Category Archives: Artificial Intelligence

The Australian Academy of Science and the Australian Academy of Law are delivering their annual joint symposium for 2021. This year the topic is Artifical Intelligence: Future directions in technology and law.

Speakers will each give a 10-minute presentation, followed by a Q&A session. The event will be moderated by The Hon Dr Annabelle Bennett AC FAA FAAL SC.

Professor Lyria Bennett Moses FAAL: Director of Allens Hub for Technology, Law and Innovation at UNSW, Sydney in the Faculty of Law and Justice. Professor Bennett Moses has written about the limitations of AI and data-driven approaches to decision-making in government, law enforcement and the legal system, and why it is crucial for everyone to understand how smart machines are impacting on our society.

Professor Sventha Venkatesh FAA FTSE: Co-Director, Applied Artificial Intelligence Institute at Deakin University, Alfred Deakin Professor, ARC Laureate Fellow, Co-Director of Applied Artificial Intelligence Institute and a leading Australian computer scientist who has made fundamental and influential contributions to the field of activity and event recognition in multimedia data.

Professor Toby Walsh FAA: Scientia Professor of Artificial Intelligence at the University of NSW a leading researcher in Artificial Intelligence, a Laureate Fellow and Scientia Professor of Artificial Intelligence in the School of Computer Science and Engineering at UNSW Sydney, and leader of the Algorithmic Decision Theory group at CSIRO Data61.

Mr Edward Santow FAAL: served as Australias Human Rights Commissioner from 2016-2021. He recently started as Industry Professor - Responsible Technology at the University of Technology Sydney. He leads a major UTS initiative to build Australias strategic capability in AI and new technology. This will support Australian business and government to be leaders in responsible innovation by developing and using AI that is powerful, effective and fair.

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Artificial Intelligence: Future directions in technology and law - Australian Academy of Science

Introduction by Croakey: As with the COVID-19 pandemic, health authorities usually identify epidemics through public health surveillance, but could we do it earlier by being able to mine the vast un-curated public data available to us in this digital age?

Thats the hope and challenge from leading epidemiologist, Professor Raina MacIntyre, who heads the Biosecurity Program at the Kirby Institute, and Arunn Jegan, Advocacy Coordinator at Mdecins Sans Frontires (MSF).

They write below on the potential for harnessing artificial intelligence and the proliferation of the internet and social media for early detection of epidemics, saying that a signal for unusual pneumonia in China could have been detected in November 2019 and that CSIRO research showed that the Ebola epidemic in West Africa could have been detected three months before the World Health Organization was aware of it.

They ask:

Imagine if the COVID-19 pandemic had been detected well before it spread around the world, when there was only a handful of cases contained within a small geographic location?

Readers may also be interested in the series of articles published by the Croakey Conference News Service from the recent World Congress of Epidemiology, with one on innovative Victorian disease surveillance measures and their critical role in the states COVID response to be published soon.

The SARS-COV2 (COVID-19) pandemic has caused devastation around the world, and even in vaccinated populations, it continues to mutate into dangerous variants of concern. With the onset of the Delta variant, we assume the death toll will rise beyond five million in 2021.

This is an epidemic disease, which means it grows exponentially. One case today will be five cases in a few days and then 25 cases and so on. So, time is of the essence, and the sooner you can identify epidemics, the better the prospect of stamping it out and preventing global spread.

Imagine if the COVID-19 pandemic had been detected well before it spread around the world, when there was only a handful of cases contained within a small geographic location?

Isolating cases and tracing and quarantining their contacts may have been enough to stop it spreading.

Exponential growth and time are the enemies we face with epidemic diseases the longer we take to act, the larger the epidemic will become and over a very short period. Just look at the Sydney outbreak which started in Bondi in June 2021.

Recall the West African Ebola epidemic in 2014. It was 67 times the size of the largest previously recorded Ebola outbreak, it reached urban areas, and killed more than 11,300 people.

Ebola outbreaks can kill 25 to 90 percent of those infected. In 2014-15, hundreds of health workers died, decimating the already-struggling healthcare systems of Liberia, Guinea, and Sierra Leone. Medecins Sans Frontieres (MSF) responded in each of these contexts.

In the Ebola outbreak, with fears of a pandemic on the horizon, organisations like the World Health Organization (WHO), MSF, and others supported national health systems by treating and isolating patients; tracing and follow up of patient contacts; raising community awareness of the disease such as how to prevent it and where to seek care; conducting safe burials; proactively detecting new cases; and supporting existing health structures.

When WHO was first notified of Ebola in March 2014, it may have comprised a few 100 cases, but it grew exponentially. By August 2014, the case numbers were in the thousands, and by October over 20,000 cases had occurred.

Furthermore, until only very recently, there were no tools to prevent or treat Ebola. Today a preventive vaccine and curative drugs are available. Imagine how many lives could have been saved if the epidemic had been detected when there were only a handful of cases.

Prior to COVID-19 in 2019, the Ebola epidemic saw the fastest trajectory to development of a vaccine, with Phase 1 trials in Oct 2014 to the approval of this vaccine in Nov 2019. Indeed, the average time was 10-15 years prior to both COVID-19 and Ebola vaccine developments.

For COVID-19, vaccines were developed and ready for use in less than 12 months, but after devastating global consequences of the pandemic and the hundreds of thousands killed in the global north.

In short, it is unwise to rely solely upon vaccines and or/ their development to manage an epidemic, especially in low-resource settings. Non-pharmaceutical interventions such as testing, tracing and measures to reduce contact between people are also important.

We have had a measles vaccine since the 1960s, however the disease rages through the world in epidemic proportions in over 41 countries such the Democratic Republic of Congo and Central African Republic.

The primary reason behind this is a deeply inequitable, and unfair global biomedical system which has unfairly provided for wealthier countries but not low-income countries.

We are seeing it play out with COVID-19, where only 1.8 per cent of people in low-income countries have received one dose, out of 5.4 billion doses administered globally.

With COVID-19, the general public have had a taste of what epidemiologists have known for decades, that strong health surveillance is essential to getting on top of outbreaks and to have any chance of zero elimination strategies, or any suppression strategy for that matter, working.

While the global disparity of vaccination rates persists, what new technologies is Australia investing in to helping communities get on-top of outbreaks and bolster health surveillance?

How are we harnessing artificial intelligence together with the proliferation of the internet and social media for early detection of epidemics?

The usual way we identify epidemics is through public health surveillance which is when labs or doctors notify health authorities of unusual, serious, or notifiable infections.

When lots of these notifications start piling up, or a trend is seen of higher case numbers than usual, the health official may investigate a possible outbreak.

But people talk about illness in their communities, and local news agencies report on unusual outbreaks, long before health officials know about it.

What if we could mine the vast, un-curated public data available to us in this digital age and detect signals of epidemics early?

At UNSW, the EpiWatch observatory does just that, tapping into news reports from around the world, in many different languages, using algorithms and artificial intelligence (AI) to detect early outbreak signals.

We showed that a signal for unusual pneumonia in China could have been detected in November 2019; and CSIRO research showed that the Ebola epidemic in West Africa could have been detected three months before WHO was aware of it.

This is in no way a replacement for in-country based data collection or existing Early Warning, and Alert Response Systems (EWARS). Using AI in epidemiology is an additional tool that uses innovative technologies and has the potential to reach communities who do not have the strongest national health surveillance systems.

It can also overcome censorship of information to detect signals in countries that are withholding outbreak information from the world. Reasons for censorship include fear of impacts on tourism, trade, or other parts of the economy, or political reasons.

Traditionally, declaring epidemics rest solely on the responsibility of governments, but never in human history has there been more attention on virology and epidemiology from the public. Therefore, ensuring that data-collected from the internet follows scientific modelling and surveying has never been more important.

As with most emergent technology using data and information to inform a product, the ethics over use of open-source data and safe-guards will need to be in place on who this empowers. Generally, however, methods such as used by Epiwatch do not utilise identifying or private information.

Moving forward the Kirby Institute at UNSW, with CSIRO Data 61 is exploring with MSF on how best AI can be utilised to detect epidemics as fast as possible and give vulnerable communities in low-income countries a fighting chance when epidemics strike.

Applying our lessons learnt from the COVID-19 pandemic and Ebola, now is the right time for Australia and the humanitarian community to invest in innovative health surveillance systems, and to keep potential epidemics isolated to save lives.

Professor Raina MacIntyre is NHMRC Principal Research Fellow and Professor of Global Biosecurity. She heads the Biosecurity Program at the Kirby Institute, which conducts research in epidemiology, vaccinology, bioterrorism prevention, mathematical modelling, genetic epidemiology, public health and clinical trials in infectious diseases.

Arunn Jegan is Advocacy Coordinator at Mdecins Sans Frontires (MSF) Australia. He is also the Permanent Facilitator for the emergency public health course at Epicentre in Paris. Arunn has worked as Head of Mission and Emergency Coordinator and has worked in Yemen, Syria, Venezuela, Bangladesh for MSF and in Afghanistan, Iraq, Jordan, Lebanon, and Turkey in senior management positions for other international NGOs. He specialises in social research, conflict/political analysis, complex project management, and humanitarian crisis coordination of public health emergencies.

See the Croakey Conference News Service coverage from the World Congress of Epidemiology.

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Harnessing artificial intelligence to help prevent epidemics before they spread - Croakey Health Media

SAN JOSE, Calif.--(BUSINESS WIRE)--Interface Masters Technologies announces Tahoe 8828, an off-the-shelf artificial intelligence and machine learning powerhouse, which rounds out Interface Masters family of ARM and MIPs based network appliances.

The modular appliance features a Marvell OCTEON TX2 ARM64 multicore processor (18 to 24-cores at 2.4GHz) as a primary CPU, and supports a range of high-performance offload processing options, as well as a single configurable I/O module supporting a range (1G to 100G) port configurations.

Optional high-performance offload processing upgrades include Interface Masters proprietary Intel based DataSlammerTM technology or any of Nvidias advanced industry-leading graphic processing units (GPUs).

Interface Masters is an OEM hardware solutions provider. Our new Tahoe 8828 is entirely designed and manufactured in the USA our Hardware is NEVER compromised and always secure, says Ben Askarinam. DataSlammer technology is an excellent fit for data intensive applications such as artificial intelligence [AI], deep packet inspection [DPI], machine learning [ML] as well as the edge compute.

As with all Interface Masters appliances, the device includes out-of-the-box support for the Marvells impressive SDK 11 Software Development Kit (SDK), and Linux. Interface Masters support for the SDK and additional built-in software and firmware enable rapid development.

Long Product Life Cycle

Interface Masters network appliance users benefit from a long-lasting product life cycle (seven-years), which enables continuity through all phases of product rollouts and servicing.

Designed and Manufactured in the United States / About Us

For over 26 years, Interface Masters Technologies has provided custom and off-the-shelf innovative networking solutions to OEMs, Fortune 100, and startup companies. Headquartered in Silicon Valley, we proudly design and manufacture all products here. Based on MIPS, ARM, PowerPC, x86 processors, and switch fabrics up to 12.8T, Interface Masters appliance models enable OEMs to significantly reduce time-to-market. Our solutions are reliable, pre-tested, pre-integrated and support a seven-year long-life cycle. Learn about Interface Masters: http://www.interfacemasters.com.

*All third-party trademarks are the property of their respective owners.

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Interface Masters Develops Industry-Leading Tahoe 8828 Network Appliance for Advanced Artificial Intelligence and Machine Learning Applications -...

By: Jonathan Wall September 8, 2021

Dont be deceived by the sleek look: Cleveland Golfs Launcher XL irons are designed for the game-improvement golfer who needs an abundance of forgiveness and technology.

The hollow cavity construction features a new variable-thickness Mainframe face that was created using Artificial Intelligence. In recent years, AI has played a larger role in the club design process as manufacturers have continued to push the boundaries, particularly when it comes to face construction.

With AI taking the lead on face design, Clevelands engineering team focused on improving the common high-toe mishit for mid-to-high handicap golfers. Compared to the previous generation, Launcher XL offers a 15 percent increase in MOI (a measure of forgiveness) on high-toe strikes in an effort to tighten the distance loss delta.

Along with adding mishit protection, AI helped locate the optimal shape, weighting, and variable thickness pattern for each iron in the set, in an effort to increase distance and forgiveness across the entire face structure.

Loft-specific grooves were also added to each face to manage spin. The 4- through 7-iron have wide, flat grooves for moderate spin, while the 8-iron through wedge feature tightly-packed, deeper laser-milled grooves to generate additional spin and friction at impact.

In terms of impact improvements, a v-shaped sole with a raised leading edge was added to allow the sole to slide through the ground with less drag. According to Cleveland, the sole geometry should make it easier for golfers with a heavy strike to maintain speed and power as the head enters and exits the turf.

An 8-gram weight was also added to the butt end of the grip for a slight counterbalance to help consistently square up the face at impact. For golfers who dont typically play counter-balanced products, the manufacturer also designed a custom configuration thats a half-inch shorter without the extra mass in the grip.

Clevelands Launcher XL irons will be available Sept. 17 and retail for $800 (7-piece steel) and $900 (7-piece graphite).

Want to overhaul your bag for 2021? Find a fitting location near you at GOLFs affiliate companyTrueSpecGolf.For more on the latest gear news and information, check out our latest Fully Equipped podcast below.

Jonathan Wall is GOLF Magazine and GOLF.coms Managing Editor for Equipment. Prior to joining the staff at the end of 2018, he spent 6 years covering equipment for the PGA Tour.

Excerpt from:

FIRST LOOK: Clevelands Launcher XL irons get the Artificial Intelligence treatment - Golf.com

Speaking at Protection Review's ProtectX5 event today (9 September), Coulson reasoned that AI could be used to improve access to data and enhance the protection buying process.

Coulson said the current process can be confusing and off-putting for many consumers, who will often have questions about how protection works, what cover they need and how much normal' costs.

"We are risking a client leaving a process puzzled, confused and probably a bit upset," he said.

"With all of these issues, how can AI step in? This is not robo advice, but using an AI-powered paraplanner can help pull in the data to answer any questions a client has about protection and how it would work for their circumstances."

Coulson reasoned this could save the adviser time, while bringing up examples and case studies appropriate to that individual client to improve their knowledge and make them feel more comfortable.

"AI is not a threat, it's an assistant", he added.

To improve this technology's engagement, Coulson said advisers should ensure their clients' data is organised and up to date.

"Let's embrace it," he told delegates. "AI is already here, let's embrace it to deliver a better experience for clients and save more time for advisers. We just need to make sure we pull together and ensure the adviser community remains at the front and centre of that process."

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ProtectX5: Artificial intelligence is a help, not a threat - COVER

MARINA DEL REY, Calif., Aug. 30, 2021 /PRNewswire/ -- The Wound Pros (https://thewoundpros.com/) today introduced its automatic wound measurement app, RITA designed to aid healthcare providers in the management and treatment of chronic, non-healing wounds. The Wound Pros is a physician owned and managed wound care company and a leading supplier of wound care dressings with a presence in 16 states across the United States.

RITA represents The Wound Pros' "high-tech" approach that leverages the power of artificial intelligence and machine learning to measure chronic non-healing wounds with pinpoint accuracy. According to Dr. Bill Releford, RITA creator and CEO of the Wound Pros, capturing highly accurate measurements is essential for delivering timely and comprehensive treatments to prevent wounds from worsening and improving healing outcomes." Clinicians just need to take a picture of a patient's wound with a smartphone or tablet and RITA will measure its size and generate professional documentation to support treatment and billing alignment. The application integrates seamlessly into The Wound Pros digital wound management platform and allows care teams to remotely monitor patients' wound progression. RITA offers online and offline capabilities to ensure efficiency and reliability regardless of network connection status.

Accurate and timely documentation is widely recognized as a frequent pain point for most wound care providers and physicians. According to Dr. Refelord: "As a wound care specialist for over 30 years, proper documentation has never been more critical for medical, legal, and insurance purposes. Within minutes, RITA can generate shareable documents for treatment teams in partnering facilities. Wound care professionals can also download reports detailing healing trends for managerial purposes." The application is also HIPAA-compliant; patients' electronic health records (EHR) are protected using highest-grade security protocols. Real-time monitoring and assessment allow for precise and robust documentation, informed clinical decision-making, and improved healing outcomes.

About The Wound Pros

The Wound Pros is a physician-owned wound care management company. It is an accredited supplier of Durable Medical Equipment, Prosthetics, Orthotics, and Supplies (DMEPOS) and a Medicare Part B provider in the United States. The company provides advanced wound care services to long-term facilities across the country, including digital wound management, mobile vascular assessment, digital supply tracking, advanced EHR systems, and advanced wound care dressings. The Wound Pros uses a "high tech" approach with AI to improve standardization and wound healing outcomes and a "high touch" approach providing human-to-human interactions for customer service and quality service delivery to its clients. Ultimately, the company is committed to its "3D" mantra that, "Better Data, Better Documentation, Leads to Better Decision."

The Wound Pros is a privately held company.

Media Contact:

Daniel Yeager

(323) 794-7543

dyeager@thewoundpros.com

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SOURCE The Wound Pros, LLC

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RITA: The Wound Pros Leverages Artificial Intelligence With Its Wound Measurement App - KPVI News 6

By Deborah Borfitz

August 31, 2021 | Artificial intelligence (AI) has been paired with one of the simplest of organismsthe nematode Caenorhabditis elegansto enlighten the scientific community about the physical and chemical properties of drug compounds with anti-aging effects, according to Brendan Howlin, reader in computational chemistry at the University of Surrey (U.K.). The predictive power of the methodology has just been demonstrated using an established database of small molecules found to extend life in model organisms.

The 1,738 compounds in the DrugAge database were broadly separated into flavonoids (e.g., from fruits and vegetables), fatty acids (e.g, omega-3 fatty acids), and those with a carbon-oxygen bond (e.g., alcohol)all heavily tied to nutrition and lifestyle choices. Pharmaceuticals could be developed based on that nutraceutical knowledge, including the importance of the number of nitrogen atoms, says Howlin.

Unlike prior efforts using AI to identify compounds that slow the aging process, Howlin used machine learning to calculate the quantitative structureactivity relationship (QSAR) of molecules. The model utilized 20% of the DrugAge compounds for the test set to learn which chemical properties were important. The information was then used on the remaining 80% to train the model to identify compounds with those properties, he explains.

As described in a recently published article in Scientific Reports (DOI: 10.1038/s41598-021-93070-6), the study builds on the work of another researcher (Diogo Barardo, University of Liverpool) who a few years ago built a random forest model to predict whether a compound would increase the lifespan of C. elegans based on data in the DrugAge database. His top-30 list of predictive molecular features referred to atom and bond counts as well as topological and partial charge properties of the substances.

The nematode is frequently used in age-related research because it has many of the organ systems present in more complex animals and has a short lifespan of 20 days, says Howlin. That makes it possible to conduct experiments that are not practical in either mice or humans.

Sideline Project

AI is now routinely employed by pharmaceutical companies in lieu of having hundreds of organic chemists testing every possible variation of every possible compound to see what works, says Howlin. In fact, AI is adding speed to virtually every stage of the drug discovery process by reducing repetitive, time-consuming tasks.

That breadth is represented by research underway at the University of Surrey, he continues, where AI-savvy scientists are helping to identify hits and leads, modify compounds to optimize their activity, predict how drugs are metabolized and affect the liver, and train the next generation of students in practical, real-world applications of machine learning algorithms.

Howlin has been actively involved in anti-aging drug design for many years now. He is one of the inventors of bi- and tri-aromatic compounds as NADPH oxidase 2 (Nox2) inhibitors, which are thought to have potential in treating a wide range of common, often age-related, diseases as well as aging itself.

NADPH oxidase is an enzyme made by the body to defend against bacterial infections, says Howlin. But if it doesnt turn off like it should, it produces oxidative stress that can damage the blood vessels and trigger diseases of aging.

The AI-based prediction model was a sideline project to see if the research team could provide industry with some drug discovery clues. Employing the latest version of the DrugAge database, it expands the number of identified molecules with anti-aging properties to 395 from the 229 previously identified by Barardo, while the volume of compounds that did not increase lifespan held steady at 1,163, Howlin reports.

Promising Leads

The study describes several compoundsthe flavonoids rutin and hesperidin (the predominant phenolic compound in orange extracts) and the organooxygen compounds lactose and sucrosewhich were previously found to be longevity-promoting in experiments on C. elegans. Future work will need to consider dosage, since it can impact whether a substance is beneficial or detrimental, he notes.

In addition to rutin (abundant in many plants), further in vivo testing may be warranted for gamolenic acid (plentiful in evening primrose oil and black currant oil), lactulose (shown to effectively treat chronic constipation in the elderly patients), and rifapentine (an antibiotic approved for the treatment of tuberculosis) based on the predictive exercise.

Moving forward, the machine learning model could be applied to any database to calculate the properties of different compounds, Howlin says. Many such databases are the property of pharmaceutical companies and could be tapped as a first step to improving human health by helping people age better.

University of Surrey researchers could also be supplementing their own aging research by finding new active compounds they can test alongside their experimental Nox2 inhibitors, he adds.

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Artificial Intelligence Calculates Anti-Aging Properties Of Compounds - Bio-IT World

Newswise Palo Alto, CA -- A study conducted by researchers at Palo Alto University has shown artificial intelligence-based chatbots to be effective as a psychological intervention in Spanish speaking university students. The study took place in Argentina and showed promising evidence for the usability and acceptability of the mental health chatbot, Tess. The findings were published by JMIR Publications, which is dedicated to advancing digital health and open science.

The studys objective was to evaluate the viability, acceptability, and potential impact of using Tess, a chatbot, for examining symptoms of depression and anxiety in Spanish speaking university students. Chatbots are a novel delivery format that can expand the mental health services offerings and facilitate early access to those in need. This represents an opportunity for addressing delays associated with access to treatment for depression and anxiety.

While research conducted in the United States has reported decreased depressive and anxiety symptoms in college students, no studies have been performed on chatbots used for addressing mental health disorders in Spanish-speaking populations, said Eduardo Bunge, PhD, and Director for the Children and Adolescent Psychotherapy and Technology (CAPT) Lab at Palo Alto University.

The study assesses the viability and acceptability of psychological interventions delivered through Tess to college students in Argentina for the most prevalent disorders in Argentina; anxiety (16.4%) and mood (12.3%) disorders. The average age for the onset of these conditions is 20 years. The Pan American Health Organization (PAHO) and the Argentinian Ministry of Health have highlighted the importance of optimizing health care services for individuals who are not receiving any form of psychological care.

Results

The initial sample consisted of 181 Argentinian college students aged 18 to 33. On an average, 472 messages were exchanged, with 116 of the messages sent from the users in response to Tess. A higher number of messages exchanged with Tess was associated with positive feedback. No significant differences between the experimental and control groups were found from the baseline to week 8 for depressive and anxiety symptoms. However, significant intragroup differences demonstrated that the experimental group showed a significant decrease in anxiety symptoms; no such differences were observed for the control group. Further, no significant intragroup differences were found for depressive symptoms.

Conclusions

The students spent a considerable amount of time exchanging messages with Tess and positive feedback was associated with a higher number of messages exchanged. The initial results show promising evidence for the usability and acceptability of Tess in the Argentinian population. Research on chatbots is still in its initial stages and further research is needed.

About Palo Alto University

Palo Alto University (PAU), a private, non-profit university located in the heart of Northern Californias Silicon Valley, is dedicated to addressing pressing and emerging issues in the fields of psychology and counseling that meet the needs of todays diverse society. PAU offers undergraduate and graduate programs that are led by faculty who make significant contributions to in their field. Online, hybrid and residential program options are available. PAU was founded in 1975 as the Pacific Graduate School of Psychology and re-incorporated as Palo Alto University in August 2009. PAU is accredited by the Western Association of Schools and Colleges (WASC). PAUs doctoral programs are accredited by the American Psychological Association (APA) and its masters in counseling programs by the Council for Accreditation of Counseling & Related Educational Programs (CACREP).

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First Study on Artificial Intelligence-Based Chatbot for Anxiety & Depression in Spanish-Speaking University Students - Newswise

We aggregated thousands of records from GlobalDatas proprietary jobs, deals, patents and company filings databases to identify the top companies in the area of artificial intelligence in the technology sector.

International Business Machines Corp and Microsoft Corp are leading the way for artificial intelligence investment among top technology companies according to our analysis of a range of GlobalData data.

Artificial intelligence has become one of the key themes in the technology sector of late, with companies hiring for increasingly more roles, making more deals, registering more patents and mentioning it more often in company filings.

These themes, of which artificial intelligence is one, are best thought of as any issue that keeps a CEO awake at night, and by tracking and combining them, it becomes possible to ascertain which companies are leading the way on specific issues and which are dragging their heels.

According to GlobalData analysis, International Business Machines Corp is one of the artificial intelligence leaders in a list of high-revenue companies in the technology industry, having advertised for 8,040 positions in artificial intelligence, made seven deals related to the field, filed 461 patents and mentioned artificial intelligence 10 times in company filings between January 2020 and June 2021.

Our analysis classified 15 companies as Most Valuable Players or MVPs due to their high number of new jobs, deals, patents and company filings mentions in the field of artificial intelligence. An additional four companies are classified as Market Leaders and zero are Average Players. Two more companies are classified as Late Movers due to their relatively lower levels of jobs, deals, patents and company filings in artificial intelligence.

For the purpose of this analysis, weve ranked top companies in the technology sector on each of the four metrics relating to artificial intelligence: jobs, deals, patents and company filings. The best-performing companies the ones ranked at the top across all or most metrics were categorised as MVPs while the worst performers companies ranked at the bottom of most indicators were classified as Late Movers.

Microsoft Corp is spearheading the artificial intelligence hiring race, advertising for 15,092 new jobs between January 2020 and June 2021. The company reached peak hiring in March 2021, when it listed 1,495 new job ads related to artificial intelligence.

International Business Machines Corp followed Microsoft Corp as the second most proactive artificial intelligence employer, advertising for 8,040 new positions. Dell Technologies Inc was third with 5,323 new job listings.

When it comes to deals, Tencent Holdings Ltd leads with 29 new artificial intelligence deals announced from January 2020 to June 2021. The company was followed by Microsoft Corp with 19 deals and Apple Inc with nine.

GlobalData's Financial Deals Database covers hundreds of thousands of M&A contracts, private equity deals, venture finance deals, private placements, IPOs and partnerships, and it serves as an indicator of economic activity within a sector.

One of the most innovative technology companies in recent months was Samsung Electronics Co Ltd, having filed 1,271 patent applications related to artificial intelligence since the beginning of last year. It was followed by Intel Corp with 505 patents and International Business Machines Corp with 461.

GlobalData collects patent filings from 100+ counties and jurisdictions. These patents are then tagged according to the themes they relate to, including artificial intelligence, based on specific keywords and expert input. The patents are also assigned to a company to identify the most innovative players in a particular field.

Finally, artificial intelligence was a commonly mentioned theme in technology company filings. Google, Inc. mentioned artificial intelligence 12 times in its corporate reports between January 2020 and June 2021. Intel Corp filings mentioned it 12 times and Microsoft Corp mentioned it 12 times.

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Which companies are leading the way for artificial intelligence in the technology sector? - Verdict

Researchers at the University of Birmingham have developed a new way to identify which patients with heart failure will benefit from treatment with beta-blockers.

Heart failure is one of the most common heart conditions, with substantial impact on patient quality of life, and a major driver of hospital admissions and healthcare cost.

The study involved 15,669 patients with heart failure and reduced left ventricular ejection fraction (low function of the hearts main pumping chamber), 12,823 of which were in normal heart rhythm and 2,837 of which had atrial fibrillation (AF) - a heart rhythm condition commonly associated with heart failure that leads to worse outcomes.

Published in The Lancet, the study used a series of artificial intelligence (AI) techniques to deeply interrogate data from clinical trials.

The research showed that the AI approach could take account of different underlying health conditions for each patient, as well as the interactions of these conditions to isolate response to beta-blocker therapy. This worked in patients with normal heart rhythm, where doctors would normally expect beta-blockers to reduce the risk of death, as well as in patients with AF where previous work has found a lack of effectiveness. In normal heart rhythm, a cluster of patients was identified with reduced benefit from beta-blockers (combination of older age, less severe symptoms and lower heart rate than average). Conversely in patients with AF, the research found a cluster of patients who had a substantial reduction in death with beta-blockers (from 15% to 9% in younger patients with lower rates of prior heart attack but similar heart function to the average AF patient).

The research was led by the cardAIc group, a multi-disciplinary team of clinical and data scientists at the University of Birmingham and the University Hospitals Birmingham NHS Foundation Trust, aiming to integrate AI techniques to improve the care of cardiovascular patients. The study uses data collated and harmonized by the Beta-blockers in Heart Failure Collaborative Group, a global consortium dedicated to enhancing treatment for patients with heart failure.

First Author Dr Andreas Karwath, Rutherford Research Fellow at the University of Birmingham and member of the cardAIc group, added: We hope these important research findings will be used to shape healthcare policy and improve treatment and outcomes for patients with heart failure.

Corresponding author Georgios Gkoutos, Professor of Clinical Bioinformatics at the University of Birmingham, Associate Director of Health Data Research Midlands and co-lead for the cardAIc group, said: Although tested in our research in trials of beta-blockers, these novel AI approaches have clear potential across the spectrum of therapies in heart failure, and across other cardiovascular and non-cardiovascular conditions.

Corresponding author Dipak Kotecha, Professor & Consultant in Cardiology at the University of Birmingham, international lead for the Beta-blockers in Heart Failure Collaborative Group and co-lead for the cardAIc group, added: Development of these new AI approaches is vital to improving the care we can give to our patients; in the future this could lead to personalised treatment for each individual patient, taking account of their particular health circumstances to improve their well-being.

The research used individual patient data from nine landmark trials in heart failure that randomly assigned patients to either beta-blockers or a placebo. The average age of study participants was 65 years, and 24% were women. The AI-based approach combined neural network-based variational autoencoders and hierarchical clustering within an objective framework, and with detailed assessment of robustness and validation across all the trials.

The research was presented this week at the ESC Congress 2021, hosted by the European Society of Cardiology - a non-profit knowledge-based professional association that facilitates the improvement and harmonisation of standards of diagnosis and treatment of cardiovascular diseases.

Notes to Editors

Link:

Artificial Intelligence approach helps to identify patients with heart failure that respond to beta-blocker treatment - University of Birmingham