CHICAGO, Oct. 5, 2022 /PRNewswire/ --Artificial Intelligence (AI) in Medical Diagnostics Marketis projected to grow from USD 1.0 billion in 2022 to USD 5.5 billion by 2027, at a CAGR of 39.9% from 2022 to 2027, according to a new report by MarketsandMarkets.The application of AI in medical diagnostics is growing at a fast pace owing to factors such as growing government initiatives to drive the adoption of AI-based technologies, rise in adoption of AI solutions by radiologists to reduce work load, the influx of big data, availability of funding for AI-based startups, and the growing number of cross-industry partnerships & collaborations.

However, the lack of a skilled AI workforce, ambiguity in regulations, and the reluctance among medical practitioners to adopt these solutions are factors expected to restrain the market growth.

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"Software segment is expected to grow at the highest rate during the forecast period."

The AI in medical diagnostics market is segmented based on components: software and services. The services segment dominated the market in 2021, while the software segment is estimated to grow at a higher CAGR during the forecast period. Software solutions help healthcare providers gain a competitive edge despite the challenges of being short-staffed and facing increasing imaging scan volumes.

"The Nurse Call system segment is estimated to account for the largest share of the global market in 2022"

The application market in AI in the medical diagnostics market is segmented into in vivo and in vitro diagnostics. The in vivo diagnostics segment commanded the largest share of 96.8% of this market in 2021. The large share of this segment can be attributed to the growing adoption of AI solutions by practitioners, as these solutions help reduce human errors and improve treatment efficacy.

"The Hospital segment is estimated to account for the largest share of the AI in medical diagnostics market."

Based on end users, the AI in medical diagnostics market is segmented into hospitals, diagnostic imaging centers, diagnostic laboratories, and other end users. The hospitals segment commanded the largest share of 64.1% of this market in 2021. The large share of hospital segment can be attributed to the rising number of diagnostic imaging procedures suggested as treatment options in hospitals, the inclination of hospitals toward the digitization of radiology patient workflow and automation of treatment procedures, rise in use of minimally invasive procedures in hospitals to focus on quality of patient care, and the rising adoption of advanced imaging modalities to improve workflow efficiency.

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"North America to dominate the AI in medical diagnostics market in 2022"

The AI in medical diagnostics market has been segmented into four main regional segments: North America, Europe, the Asia Pacific, and the Rest of the World. In 2021, North America accounted for the largest market share of this market.

However, the Asia Pacific market is projected to register the highest CAGR during the forecast period. The high growth rate of the Asia Pacific market can primarily be attributed to the growth strategies companies adopt in emerging markets, improved medical diagnostics infrastructure, rising geriatric population, increasing prevalence of cancer, and the implementation of favorable government initiatives.

Prominent players in this artificial intelligence in medical diagnostics market are Microsoft (US), NVIDIA (US), IBM (US), Intel Corporation (US), Google, Inc.(Subsidiary of Alphabet, Inc) (US), Siemens Healthineers (Germany), GE Healthcare (US), Digital Diagnostics, Inc (US), Xilinx (US), InformAI LLC (US), HeartFlow, Inc (US), Enlitic, Inc (US), Day Zero Diagnostics, Inc(US), Aidence (Netherlands), Butterfly Network, Inc. (US), Prognos Health (US), Nanox AI (Israel), Viz.ai, Inc (US), Quibin (Spain), Qure.ai (India), Therapixel (France), Aidoc (Israel), Koninklijke Philips N.V. (Netherlands), Lunit. Inc (South Korea), EchoNous Inc. (US).

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DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence Market in the Education Sector in US 2022-2026" report has been added to ResearchAndMarkets.com's offering.

The artificial intelligence market in the education sector is poised to grow by $374.3 mn during 2022-2026, accelerating at a CAGR of 48.15% during the forecast period. The report on the artificial intelligence market in the education sector provides a holistic analysis, market size and forecast, trends, growth drivers, and challenges, as well as vendor analysis covering around 25 vendors.

The report offers an up-to-date analysis of the current country market scenario, the latest trends and drivers, and the overall market environment. The market is driven by increasing demand for ITS.

The artificial intelligence market in the education sector analysis includes the end-user segment and geographic landscape.

The artificial intelligence market in the education sector is segmented as below:

By End-user

By Type

This study identifies the increased emphasis on chatbots as one of the prime reasons driving the artificial intelligence market in the education sector growth during the next few years. Also, growing emphasis on crowdsourced tutoring and increasing emphasis on content analytics will lead to sizable demand in the market.

The report on the artificial intelligence market in the education sector covers the following areas:

Key Topics Covered:

1 Executive Summary

2 Market Landscape

3 Market Sizing

4 Five Forces Analysis

5 Market Segmentation by End-user

6 Market Segmentation by Type

7 Customer Landscape

8 Drivers, Challenges, and Trends

9 Vendor Landscape

10 Vendor Analysis

11 Appendix

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/jeorof

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U.S. Artificial Intelligence Market in the Education Sector to Grow by $374.3 Million During 2022-2026 - ResearchAndMarkets.com - Business Wire

NEW YORK, Oct. 4, 2022 /PRNewswire/ -- The artificial intelligence (AI) market size in the BFSI sector is set to grow by $32.97 bn between 2021 and 2026, progressing at a CAGR of 36.68%. According to Technavio, the market is fragmented, and the degree of fragmentation will accelerate during the forecast period. As market growth over the next five years is expected to remain high, the competitive rivalry among market vendors will remain limited. To know more about the vendor landscape Read Sample PDF Report Before Purchasing.

Technavio has announced its latest market research report titled Global Artificial Intelligence (AI) Market in BFSI Sector 2022-2026

The report identifies Alphabet Inc., Amazon.com Inc., Amelia US LLC, Baidu Inc, Glia Technologies Inc, Inbenta Technologies Inc., Intel Corp., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., NVIDIA Corp., Oracle Corp., Palantir Technologies Inc., Salesforce Inc., ServiceNow Inc., Verint Systems Inc, ZestFinance Inc, and SAP SEare some of the major market participants. Although the Enhanced operational efficiency with AI will offer immense growth opportunities, the need for high data quality will challenge the growth of the market participants. To make the most of the opportunities, market vendors should focus more on the growth prospects in the fast-growing segments, while maintaining their positions in the slow-growing segments.

Artificial Intelligence (AI) Market in BFSI Sector 2022-2026: Segmentation

Artificial Intelligence (AI) Market in BFSI Sector is segmented as below:

The artificial intelligence (AI) market share growth in the BFSI sector by the banking segment will be significant during the forecast period. The use of cognitive technology, along with AI, helps banks to leverage digitalization and sustain competition with FinTech players. AI technologies are revolutionizing banking processes and the relationship between banks and customers. AI is expected to shape the future of the banking sector as it provides the power of advanced data analytics to fight against fraudulent transactions and improve compliance, all within seconds.

Story continues

48% of the market's growth will originate from North America during the forecast period. The early adoption and increasing investments in AI technologies by players such as IBM, Google, Microsoft, and AWS in the region will facilitate the artificial intelligence (AI) market growth inBFSI sector in North America over the forecast period. This market research report entails detailed information on the competitive intelligence, marketing gaps, and regional opportunities in store for vendors, which will assist in creating efficient business plans. Our artificial intelligence (ai) market in BFSI sector report covers the following areas:

Artificial Intelligence (AI) Market in BFSI Sector 2022-2026: Vendor Analysis

We provide a detailed analysis of around 25 vendors operating in the Artificial Intelligence (AI) Market in BFSI Sector, including some of the vendors such as vendors Backed with competitive intelligence and benchmarking, our research reports on the Artificial Intelligence (AI) Market in BFSI Sector are designed to provide entry support, customer profile and M&As as well as go-to-market strategy support.

Artificial Intelligence (AI) Market in BFSI Sector 2022-2026: Key Highlights

CAGR of the market during the forecast period 2022-2026

Detailed information on factors that will assist artificial intelligence (AI) market in BFSI sector growth during the next five years

Estimation of the artificial intelligence (AI) market in BFSI sector size and its contribution to the parent market

Predictions on upcoming trends and changes in consumer behavior

The growth of the artificial intelligence (AI) market in BFSI sector

Analysis of the market's competitive landscape and detailed information on vendors

Comprehensive details of factors that will challenge the growth of the artificial intelligence (AI) market in BFSI sector vendors.

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Artificial Intelligence (AI) Market In BFSI Sector Scope

Report Coverage

Details

Page number

120

Base year

2021

Forecast period

2022-2026

Growth momentum & CAGR

Accelerate at a CAGR of 36.68%

Market growth 2022-2026

$32.97 billion

Market structure

Fragmented

YoY growth (%)

33.99

Regional analysis

North America, APAC, Europe, Middle East and Africa, and South America

Performing market contribution

North America at 48%

Key consumer countries

US, Canada, China, Japan, and UK

Competitive landscape

Leading companies, competitive strategies, consumer engagement scope

Companies profiled

Alphabet Inc., Amazon.com Inc., Amelia US LLC, Baidu Inc, Glia Technologies Inc, Inbenta Technologies Inc., Intel Corp., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., NVIDIA Corp., Oracle Corp., Palantir Technologies Inc., Salesforce Inc., ServiceNow Inc., Verint Systems Inc, ZestFinance Inc, and SAP SE

Market Dynamics

Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and future consumer dynamics, and market condition analysis for the forecast period.

Customization purview

If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized.

Table Of Contents :

1 Executive Summary

2 Market Landscape

3 Market Sizing

4 Five Forces Analysis

5 Market Segmentation by End-user

6 Customer Landscape

7 Geographic Landscape

8 Drivers, Challenges, and Trends

9 Vendor Landscape

10 Vendor Analysis

11 Appendix

About Us

Technavio is a leading global technology research and advisory company. Their research and analysis focus on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions. With over 500 specialized analysts, Technavio's report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio's comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

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Technavio ResearchJesse MaidaMedia & Marketing ExecutiveUS: +1 844 364 1100UK: +44 203 893 3200Email: media@technavio.comWebsite: http://www.technavio.com/

Global Artificial Intelligence (AI) Market in BFSI Sector 2022-2026

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Artificial Intelligence (AI) Market in BFSI Sector to Record USD 32.97 Billion growth between 2021 and 2026; Major Opportunities with Alphabet Inc....

There's nothing that blurs the line between frightening and fascinatingquitelike artificial intelligence.

And since artificial intelligence and electronic music are becoming moresymbiotic by the day, the staff here at EDM.comwanted to see just how far it could go in a visual sense. So we came up with bizarre descriptions of artists and fed them through A.I. art generators.

Some images are photorealistic. Others arefancifullydistorted. And the majority of them are flat-out creepy.

But we digress. Read on to see our weird and wonderful creations.

"TOKiMONSTA DJing in a neon sky arcade with golden canaries" by Jason Heffler.

Jason Heffler

"REZZ DJ as painted by Salvador Dal" by Nick Yopko.

Nick Yopko

"Flume creating his latest album in a psychedelic jungle" by Koji Aiken.

Koji Aiken

"Martin Garrix in his studio at the top of a cyberpunk skyscraper" by Konstantinos Karakolis.

Konstantinos Karakolis

"CloZee DJs underwater with neon jellyfish"byShakiel Mahjouri.

Shakiel Mahjouri

Charlotte de Witte DJing in a hurricane of music by Tessa Frey.

Tessa Frey

"TroyBoi DJing inside a technicolor candy shop rave"by Carlie Belbin.

Carlie Belbin

"Lane 8 DJing on top of a giant mushroom" by Mikala Lugen.

Mikala Lugen

"Daft Punk baking a cake on the moon" by Jarett Lopez.

Jarett Lopez

Shaq DJing at the base of an active volcano site with lightning in the sky by Cameron Sunkel.

Scroll to Continue

Cameron Sunkel

"Marc Rebillet in a robe in Manhattan singing to a sea of psychedelic flamingos"by Leah McClure.

Leah McClure

Porter Robinson DJing deep in the ocean while gasping for the last sight of sky" by Grecco Costamagna.

Grecco Costamagna

Mija DJing in a post-apocalyptic, punk rock cyberpunk dystopian rave by Brian Rapaport.

Brian Rapoport

"Calvin Harris playing piano on a rowboat in outer space" by Kyle B. Jones.

Kyle B. Jones

"Inside of a tropical coconut, Kygo plays a glittery piano surrounded by glowing flamingos"by Brooke Bierman.

Brooke Bierman

"Dillon Francis and a colorful piatawalking through a futuristic cityscape"- by Lennon Cihak.

Lennon Cihak

Perhaps no artist is more fitting for this A.I. endeavor than the iconic Aphex Twin, whose metaphysically madcap aesthetic chills the collective spine of the music industry to this day. Sowe had a little too much fun.

"Aphex Twin creating his own twisted synthesizer in a dystopian depraved hellscape surrounded by strange dark followers" by Saad Masood.

Saad Masood

Saad Masood

Saad Masood

"Aphex twin performs in a dystopian depraved hellscape for a crowd of dark souls" bySaad Masood.

Saad Masood

Saad Masood

Saad Masood

Editor's Note: The images in this article were generated usingWonder and Dream by WOMBO.

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We Came Up With Bizarre Descriptions of DJsThen Used Artificial Intelligence to Bring Them to Life - EDM.com

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence in Diabetes Management Market (2022-2027) by Device, Technique, and Geography, with Competitive Analysis, Impact of COVID-19, and Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence in Diabetes Management Market is estimated to be worth USD 590.32 million in 2022, and is expected to reach USD 2,235.15 million by 2027, growing at a CAGR of 30.51%.

Market dynamics are forces that impact the prices and behaviors of the stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors.

There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals. As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

The Competitive Quadrant

The report includes the Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

Why Buy This Report?

Market Dynamics

Drivers

Restraints

Opportunities

Challenges

Market Segmentation

The Global Artificial Intelligence in Diabetes Management Market is segmented based on Device, Technique, and Geography.

Companies Mentioned

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The Worldwide Artificial Intelligence in Diabetes Management Industry is Expected to Reach $2.2 Billion by 2027 - ResearchAndMarkets.com - Business...

Thanks to the internet and social networks, we now have real-time access to global dialogues, trends, and news; by using artificial intelligence to create art based on contemporary debate topics, Woods Art Institutes The Art of Trending project examines the boundaries of art and what it is that makes an artist.

The institute describes it as the most contemporary art exhibition, curated by all of us and executed by AI.

It is impressive and frightening at the same time how far artificial intelligence has come in this area. The many questions that this raises for our industry are what I find particularly fascinating, Managing Director of INGO Hamburg Tobias Ahrans tells Impakter.

Launched in cooperation with creative agency INGO Hamburg and MAGIG Design + Technologies, the campaign began on September 19 on the Woods Art Institutessocial platforms and billboards around Germany. Due to its success, it has been extended and will last until the end of October.

The Art of Trendingsoftware employs hashtags gleaned from social listening to determine what is genuinely trending, notably in the realms of society, culture, the environment, and politics. The rest is pretty simple: Artificial Intelligence program DALL-E 2, which creates digital images from text descriptions, turns the hashtags or debate topics into artwork.

The open AI use policy prohibits DALL-E 2 from generating any inappropriate material.

Below are some examples of contemporary debate topics turned into art by artificial intelligence digital image generator DALL-E 2 as part of The Art of Trending project.

Recognizing that the art business is not an exception and that, like with any other sector, AI could eventually threaten artists jobs, Woord Art Institute explains that they dont view the technology as a job replacement but rather as a powerful tool for visual designers that embraces and understands.

As Ahrans tells us, the institute finds the experiment interesting not only on what AI can do but about sparking a conversation around new technologies related to art.

At the end of the day, our goal is to fuel a conversation with this experiment, Ahrans adds.

Furthermore, as tech art becomes more widely available and human art becomes more distinctive, the institute expects that AI image generators will in fact elevate the value of genuine artists work.

Interested in reading more about artificial intelligence making art? Last month, an AI-made work won a fine arts competition in the US. See here:

Art Made by AI Wins Fine Arts Competition

Editors Note:The opinions expressed here by the authors are their own, not those of Impakter.comIn the Featured Photo:Artificial intelligence generates digital image of: Iran Protests. Featured Photo Credit: Woods Art Institute.

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'The Art of Trending': AI Creating Artwork From Topics Trending on Twitter - Impakter

The EU Artificial Intelligence Act (AI Act), proposed by the European Commission in April 2021, is an ambitious and welcome attempt to develop rules for artificial intelligence, and to mitigate its risks. The current text, however, is based on a linear view of the AI value chain, in which one entity places a given AI system on the market and is made accountable for complying with the regulation whenever the system is considered high risk. In reality, the AI value chain can present itself in a wide variety of configurations. In this paper, in view of the many limitations of the Act, we propose a typology of the AI value chain featuring seven distinct scenarios, and discuss the possible treatment of each one under the AI Act. Moreover, we consider the specific case of general-purpose AI (GPAI) models and their possible inclusion in the scope of the AI Act, and offer six policy recommendations.

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Reconciling the AI Value Chain with the EU's Artificial Intelligence Act - CEPS

Chicago, Oct. 06, 2022 (GLOBE NEWSWIRE) -- According to the new market research report by MarketsandMarkets, theArtificial Intelligence In Genomics Market is projected to reach USD 1,671 million by 2025 from USD 202 million in 2020, at a CAGR of 52.7% between 2020 and 2025. The need to control drug development and discovery costs and time, increasing public and private investments in AI in genomics, and the adoption of AI solutions in precision medicine are driving the growth of this market. However, the lack of a skilled AI workforce and ambiguous regulatory guidelines for medical software are expected to restrain the market growth during the forecast period.

Browse in-depth TOC on "Artificial Intelligence (AI) in Genomics Market"141 Tables24 Figures154 Pages

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List of Key Players in Artificial Intelligence in Genomics Industry:

Drivers, Restraints, Challenges and Opportunities in Artificial Intelligence in Genomics Industry:

Key Findings of Artificial Intelligence in Genomics Market Study:

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Based on offering, the AI in genomics market is segmented into software and services. The software and services segment accounted for largest share of the global artificial intelligence in genomics market in 2019. Software is needed to generate new insights from large-scale datasets and help understand genomic variations, thus enhancing the search for disease-causing variants and reducing clinical analysis times. The benefits offered by AI in software are driving its adoption among end users.

Based on functionality, the AI in genomics market is segmented into genome sequencing, gene editing, clinical workflows, and predictive genetic testing & preventive medicine. Genome sequencing was the largest functionality segment in this market in 2019 and is estimated to grow at highest CAGR in coming years. The large share of this segment can be attributed to the use of AI solutions to identify chromosomal disorders, dysmorphic syndromes, teratogenic disorders, and single-gene disorders.

Geographical Growth Scenario:

The global AI in Genomics market is segmented into North America, Asia Pacific, Europe, Rest of the World. North America (comprising the US, and Canada) is expected to account for the largest share of the global AI in Genomics market in 2020, followed by Europe. The large share of North America can be attributed to the increasing research funding and government initiatives for promoting precision medicine in the US.

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Artificial Intelligence in Genomics Market worth $1,671 million by 2025 says MarketsandMarkets - Benzinga

For millennia, humans have imposed themselves on nature or other humans by mastering the art of melting and mixing metals: the Copper Age was followed by the Bronze or Iron Age. Modern steel is at the base of the Industrial Revolution of the late 18th and 19th centuries. In the 20th century, aluminum alloys, titanium or superalloys allowed enormous technological leaps in cars, planes, missiles, prostheses In the second decade of this millennium, a machine has discovered several alloys that equal and even surpass those created by humans in some of its properties.

A group of researchers from prestigious European technical research centers, from the Max Planck Institute for Metallurgical Research to the Delft University of Technology, passing through the Royal Institute of Technology in Stockholm, have now created a machine learning system (machine learning , in English) capable of diving among millions of combinations between the different elements of the periodic table, finding 1,000 candidates with the properties that interested them and analyzing them looking for those that theoretically would have a low coefficient of thermal expansion (the expansion or contraction of the material with cold or heat). As published in the magazine Sciencefound four new alloys with a coefficient equal to or lower than the most temperature-immune combinations used so far.

Until a few years ago, an alloy was essentially a mix between a parent metal and small concentrations of other elements from the periodic table. The rules of metallurgy almost forbade going further. The director of IMDEA Materials, Jos Manuel Honrubia, exemplifies this by comparing a coffee with an alloy based on iron. By dissolving the sugar, you get a single liquid with properties different from those of coffee and sugar separately. In alloys it is similar, but there are limits to the proportion of other elements that you can add to iron before there are precipitates that are no longer part of the main alloy and generally worsen its properties. All of this was blown up in 2004: Then two independent groups combined five elements in similar proportions, seeing that they formed a single unique solution, he says. This opened a new era in materials science, that of high-entropy alloys. But there was a new challenge: finding new combinations between a main element and smaller quantities of two or three others (steel is iron with three or four additions) was a difficult task, but feasible. Before this time, the addition of many alloying elements in large proportions was a problem. In those of high entropy, the possible new compositions of dozens of elements and their different concentrations are estimated to exceed 10. An amount impossible for humans to handle, but less so for machines.

Compared to traditional methods, machine learning is much more efficient, saving time and effort

Ziyuan Rao, scientist at the Max Planck Institute for Metallurgical Research

The researcher at the Max Planck Institute and first author of the research, Ziyuan Rao comments on the main advantage of his artificial intelligence (AI) system: Compared to traditional methods, machine learning is much more efficient, saving time and effort , He says. For most of history, the discovery of new alloys with better properties has been based on trial and error, the knowledge accumulated by craftsmen or directly serendipity. This is the case of Toledo steel, whose swords were feared for centuries. As the director of the National Center for Metallurgical Research (CENIM-CSIC) Carlos Capdevila recalls, they forged them with charcoal from nearby mountains, which contained more carbon than other swords in Europe, giving them more hardness. Materials science currently relies on computer programs and models that save calculations and anticipate results, but the decisive work remains human.

Rao and his colleagues artificial intelligence system consists of three basic steps. They first use a model that generates new mixtures from a database that the researchers had previously assembled. This is because high-entropy alloys have a huge compositional spectrum and it is almost impossible to cover all possible compositions, he details. In a second step, they use another model to predict the properties of the compositions they obtained in the first. In a final step, the system scores the candidates (in this case 1,000) by combining the expected coefficient of each with their degree of novelty.

They thus arrived at four new alloys that they compared with invar. It is an alloy that, in its original mixture, had 64% iron, another 36% nickel and small amounts of manganese, carbon and chromium. Discovered at the end of the 19th century, whose discovery earned the Nobel Prize for its creator, the Swiss Charles douard Guillaume, it had a very low coefficient of thermal expansion. Not being affected by thermal changes, it was and still is essential in the design of precision instruments, clocks, pendulums, motor valves, mechanics of telescope optics Rao assures that two of the alloys created by their intelligence system equals invar alloys and two others have the lowest coefficient of thermal expansion of high or medium entropy alloys.

Stefan Bauer, a researcher at the Royal Institute of Technology in Stockholm and one of the senior authors of this research, recalls in a note: Machine learning models have been incredibly successful when unlimited amounts of data are available, for example in video games. . However, in the real world, it is much more difficult to find use cases where artificial intelligence makes a difference. It is very exciting to see that the predictions were not only tested in simulations, but that new alloys were created and physically demonstrated. Having proven its worth with thermal expansion, the scientists intend to use their machine learning system to investigate other properties, such as magnetism, in other materials.

Jon Mikel Snchez is a researcher in advanced materials at Tecnalia. A few years ago he did his doctoral thesis on high-entropy alloys. When he is asked about the possible properties beyond thermal expansion of these alloys and their possible applications, he almost runs out of paper. There are so many alloys that have improved the traditional ones in many aspects. Some scientists compare the discovery of it with that of steels. Some have better magneto-thermal properties. Others have better cryogenic performance, key for fuel storage. He also recalls a high-entropy titanium alloy that outperforms the best titanium alloy used in prosthetics today. Lastly, one of the most important and the one that mortals understand best, better structural properties (vehicle parts, for example) especially at high temperatures. Hence, Snchez believes, the relevance of these works. Applying AI to discover new alloys is quite new. Discovering new materials by these methods is a significant advance, he says.

Capdevila, the director of CENIM, comments that discovering a new alloy or improving the properties of existing ones by slightly modifying their composition has its advantages. He gives the example of the cover that they are going to put on the Santiago Bernabu soccer field. Stainless steels have a high reflectance and without modifying them, the temperature on the surrounding terraces would be very high. However, the alloy they will put in neutralizes most of the heat. Discovering a new alloy would be for a doctoral thesis of four or five years, now the machine does it in a few days. But Capdevila emphasizes that the human part is still there. Its computing power, but I, human, tell it what parameters interest me.

Torralba, the director of IMDEA Materials, is convinced that high entropy alloys are beginning a new era. They promise improvements in highly demanded properties, such as certain magnetic properties, high resistance to corrosion, greater tolerance to extreme temperatures or thermal changes and remember that one of the obstacles to the development of fusion energy is the lack of a material that can withstand the high temperatures generated in a fusion reactor. In all technologies, progress depends on the necessary materials being available, he recalls.

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Artificial intelligence discovers the 'toledano steel' of the future - Morning Express

A panel of physicians and leaders in the field expressed enthusiasm for AIs possible benefits for patients. They also said solutions must be designed with health equity in mind.

Many have hailed the potential of artificial intelligence to transform healthcare.

Michael Howell, Googles chief clinical officer and deputy chief health officer, says, Its hard to imagine a technology that is more hyped than AI.

Even so, Stephen Parodi, executive vice president of The Permanente Federation, says, Widespread AI use in healthcare is still in its infancy.

Still, many are projecting significant growth in the prevalence of AI in medicine in the near future.

During a one-hour forum hosted by The Permanente Federation Monday, healthcare leaders, all physicians, assessed the possibilities of AI, the keys to success, and expectations on its future uses.

Even in a forum where leaders talked about potential challenges, including designing technology with patients in mind and the urgent need to focus on equity, the participants spoke with enthusiasm, even excitement, about the growing role of artificial intelligence in medicine.

Its appropriate to bring some healthy skepticism and ask questions about the potential of artificial intelligence in healthcare, Howell said.

However, Howell also said he expected, AI will do things we didnt think were possible.

Earlier interventions

Edward Lee, executive vice president and chief information officer of The Permanente Federation, talked about how AI is being used across the Kaiser Permanente system.

At Kaiser Permanente, researchers have used AI to examine retinal images of patients with diabetes, to possibly determine if patients are more likely to lose their vision, Lee said.

In addition, Kaiser Permanente is using AI-powered models to analyze which patients in hospitals may be at higher risk of deteriorating or could require intensive care. "This gives us a chance to intervene before patients get sicker, Lee said.

Hundreds of patients have likely been saved, he said, and thats a conservative estimate.

The system is using AI to analyze emails to make sure they are getting to the right member of the care team. This helps our patients get timely responses to their health concerns, Lee said.

John Halamka, president of Mayo Clinic Platform, said he expected that within the next six quarters, artificial intelligence is going to be brought into the workflow of electronic health records.

The Mayo Clinic has been increasingly using AI in research. Mayo Clinic researchers have been studying the use of artificial intelligence to identify pregnant patients who may be at risk for complications, as well as patients who could have greater likelihood of suffering a stroke.

When asked about when AI would gain greater prevalence, Halamka cited the author William Gibson, who once said, The future is already here, its just not evenly distributed.

I believe the perfect storm for innovation requires technology thats good enough, policy thats enabling and cultural change that creates a sense of urgency, Halamka said.

Patients have greater expectations of healthcare, and that will help expand the use of AI in medicine, panelists said. The cultural demands of our patients will drive us forward, Halamka added.

Google Health is using artificial intelligence to bring better technology to care teams, and also in reaching out to consumers when theyre searching for health information online, steering them to relevant and accurate results and away from misinformation, Howell said. The tech giant is also using AI in community context, he said, such as better projections of flood threats.

Vivian Lee, president of health platforms at Verily, a sister company of Google, talked about the use of AI algorithms to identify patients at higher risk of hypertension, substance use, or a longer hospital stay. She said the goal is getting that information to the clinicians to make that data more actionable.

Artificial intelligence also presents opportunities to engage patients in different ways, and that goes beyond just personalized medicine, Vivian Lee said. With AI, she said the question becomes, How do we move to precision health and precision engagement?

I really believe the advances we are making now will enable us to do personalized care at scale, Vivian Lee said.

During the forum, participants, including the audience weighed in on where AI would have the most potential to improve healthcare. Most said it would be the use of artificial intelligence to predict potential health risks.

I think the thing about risk prediction is it can affect not only individual patients it can affect entire populations, entire communities, Edward Lee said. We can positively contribute to the health of many, many patients.

Focusing on health equity

Even as the panelists touted AIs promise, they also said health systems aiming to use artificial intelligence must focus on closing healthcare disparities.

There is deep evidence that care that isnt equitable just isnt high quality, Howell said.

Everyone should have the opportunity to receive the full benefits of AI We should work systematically to make sure that happens," he said.

Researchers are using artificial intelligence to predict risks in patients, but as Howell noted, the problem is some data is missing when it comes to patients from underrepresented communities. In a sense, disparities can be baked into the data being analyzed.

Vivian Lee shared similar concerns. We need to be attentive to bias and health equity, she said.

Fatima Paruk, chief health officer and senior vice president of Salesforce, said AI could be both an enabler or a barrier. But she said, It leaves me thinking we can deliver more equitable care.

The technology of AI in and of itself is only so useful, Edward Lee said.

Combining with expertise is when you can really make a difference in the lives of the patients, he said.

The panels members said they were hopeful in part because much of the research in AI and the new artificials intelligence are being developed by those in the healthcare industry.

Paruk touted AIs potential, combined with remote patient monitoring, in helping older patients potentially live at home longer. Health systems could eventually use data to get a sense of when those older patients may need more assistance.

That would also be a boon to many in the sandwich generation, who are caring for both their children and aging parents. Theres a huge amount of potential there, she said.

While panel members noted similar predictions about electronic medical records reducing demands on physicians, Paruk and others said AI could reduce burnout among clinicians.

But ultimately, the panel members expressed the most enthusiasm for how artificial intelligence could transform patient care.

Im incredibly hopeful for the future, Paruk said.

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Artificial intelligence and its potential to change healthcare - Chief Healthcare Executive