The AI tool, called Mia, was piloted alongside NHS clinicians in the UK and analysed the mammograms of over 10,000 women. 

Most of the participants were cancer-free, but the AI successfully flagged all of those with symptoms of breast cancer—as well as an additional 11 cases that the doctors failed to identify. Of the 10,889 women who participated in the trial, only 81 chose not to have their scans reviewed by the AI system.

The AI tool was trained on a dataset of over 6,000 previous breast cancer cases to learn the subtle patterns and imaging biomarkers associated with malignant tumours. When evaluated on the new cases, it correctly predicted the presence of cancer with 81.6 percent accuracy and correctly ruled it out 72.9 percent of the time.

Breast cancer is the most common cancer in women worldwide, with two million new cases diagnosed annually. While survival rates have improved with earlier detection and better treatments, many patients still experience severe side effects like lymphoedema after surgery and radiotherapy.

Researchers are now developing the AI system further to predict a patient’s risk of such side effects up to three years after treatment. This could allow doctors to personalise care with alternative treatments or additional supportive measures for high-risk patients.

The research team plans to enrol 780 breast cancer patients in a clinical trial called Pre-Act to prospectively validate the AI risk prediction model over a two-year follow-up period. The long-term goal is an AI system that can comprehensively evaluate a patient’s prognosis and treatment needs.

(Photo by Angiola Harry)

See also: NVIDIA unveils Blackwell architecture to power next GenAI wave 

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post AI tool finds cancer signs missed by doctors appeared first on AI News.

During the discussion, Grande provided insightful perspectives on the current challenges, how Edge Impulse is helping address these struggles, and the tremendous promise of on-device AI.

Key hurdles with edge AI adoption

Grande highlighted three primary pain points companies face when attempting to productise edge machine learning models, including difficulties determining optimal data collection strategies, scarce AI expertise, and cross-disciplinary communication barriers between hardware, firmware, and data science teams.

“A lot of the companies building edge devices are not very familiar with machine learning,” says Grande. “Bringing those two worlds together is the third challenge, really, around having teams communicate with each other and being able to share knowledge and work towards the same goals.”

Strategies for lean and efficient models

When asked how to optimise for edge environments, Grande emphasised first minimising required sensor data.

“We are seeing a lot of companies struggle with the dataset. What data is enough, what data should they collect, what data from which sensors should they collect the data from. And that’s a big struggle,” explains Grande.

Selecting efficient neural network architectures helps, as does compression techniques like quantisation to reduce precision without substantially impacting accuracy. Always balance sensor and hardware constraints against functionality, connectivity needs, and software requirements.

Edge Impulse aims to enable engineers to validate and verify models themselves pre-deployment using common ML evaluation metrics, ensuring reliability while accelerating time-to-value. The end-to-end development platform seamlessly integrates with all major cloud and ML platforms.

Transformative potential of on-device intelligence

Grande highlighted innovative products already leveraging edge intelligence to provide personalised health insights without reliance on the cloud, such as sleep tracking with Oura Ring.

“It’s sold over a billion pieces, and it’s something that everybody can experience and everybody can get a sense of really the power of edge AI,” explains Grande.

Other exciting opportunities exist around preventative industrial maintenance via anomaly detection on production lines.

Ultimately, Grande sees massive potential for on-device AI to greatly enhance utility and usability in daily life. Rather than just raw data, edge devices can interpret sensor inputs to provide actionable suggestions and responsive experiences not previously possible—heralding more useful technology and improved quality of life.

Unlocking the potential of AI on edge devices hinges on overcoming current obstacles inhibiting adoption. Grande and other leading experts provided deep insights at this year’s AI & Big Data Expo on how to break down the barriers and unleash the full possibilities of edge AI.

“I’d love to see a world where the devices that we were dealing with were actually more useful to us,” concludes Grande.

Watch our full interview with Alessandro Grande below:

(Photo by Niranjan _ Photographs on Unsplash)

See also: AI & Big Data Expo: Demystifying AI and seeing past the hype

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post AI & Big Data Expo: Unlocking the potential of AI on edge devices appeared first on AI News.

This collaboration will capitalise on Absci’s Integrated Drug Creation platform—seamlessly integrating with AstraZeneca’s expertise in oncology, aiming to expedite the discovery of a potentially game-changing cancer therapy.

Under the agreement, Absci will deploy its pioneering generative AI technology to craft a therapeutic candidate antibody tailored for a specific oncology target. The collaboration encompasses an upfront commitment, substantial R&D funding, milestone payments, and royalties on future product sales.

Sean McClain, Founder & CEO of Absci, said: “AstraZeneca is a leader in developing novel treatments in oncology, and we are excited to collaborate with them to design a therapeutic candidate antibody with the potential to improve the lives of cancer patients.”

Absci’s Integrated Drug Creation platform combines generative AI and scalable wet-lab technologies, generating proprietary data by scrutinising millions of protein-protein interactions. This data fuels Absci’s proprietary AI models, facilitating the design of antibodies that are later validated through wet-lab experiments.

This accelerated approach, completing the entire cycle within approximately six weeks, enhances the probability of successful development outcomes for biologic drug candidates.

Puja Sapra, PhD, SVP of Biologics Engineering & Oncology Targeted Delivery at AstraZeneca, commented: “This collaboration is an exciting opportunity to utilise Absci’s de novo AI antibody creation platform to design a potential new antibody therapy in oncology.”

The announcement follows Absci’s recent publication on the design and validation of de novo antibodies using their state-of-the-art ‘zero-shot’ generative AI model.

The collaboration between Absci and AstraZeneca should further help to demonstrate how AI can be used to revolutionise drug discovery.

(Photo by National Cancer Institute on Unsplash)

See also: AI & Big Data Expo: AI’s impact on decision-making in marketing

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with Cyber Security & Cloud Expo and Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Absci and AstraZeneca forge AI partnership to discover cancer treatments appeared first on AI News.

According to a study conducted by BSI, 54 percent of UK respondents expressed excitement about AI’s potential to revolutionise medical diagnoses and 43 percent welcomed AI’s role in reducing food waste. However, there is a prevailing lack of trust.

This scepticism could hinder the integration of AI technologies in the NHS, which is currently grappling with challenges like the COVID-19 backlog and an ageing population. Almost half of Britons (49%) support the use of AI to alleviate pressure on the healthcare system and reduce waiting times. However, only 20 percent have more confidence in AI than humans in detecting food contamination issues.

The study also highlighted a pressing need for education, as 65 percent of respondents felt patients should be informed about the use of AI tools in diagnosis or treatment. 37 percent of respondents expect to use AI regularly in medical settings by 2030.

Craig Civil, Director of Data Science and AI at BSI, said:

“The magnitude of ways AI can shape the UK’s future means we are seeing some degree of hesitation of the unknown. This can be addressed by developing greater understanding and recognition that human involvement will always be needed if we are to make the best use of this technology, and by ensuring we have frameworks that are in place to govern its use and build trust.

Now is the moment for the UK to collaborate to balance the great power of this tool with the realities of actually using it in a credible, authentic, well-executed, and well-governed way.

Closing the confidence gap and building the appropriate checks and balances can enable us to make not just good but great use of AI in every area of life and society.”

60 percent believed consumers needed protections regarding AI technologies. The study also revealed that 61 percent of Britons are calling for international guidelines to ensure the safe use of AI. This demand reflects a global sentiment, with 50 percent of respondents highlighting the need for ethical safeguards on patient data use.

Harold Pradal, Chief Commercial Officer at BSI, commented:

“AI is a transformational technology. For it to be a powerful force for good, trust needs to be the critical factor. There is a clear opportunity to harness AI to drive societal impact, change lives, and accelerate progress towards a better future and a sustainable world.

Closing the AI confidence gap is the first necessary step, it has to be delivered through education to help realise AI’s benefits and shape Society 5.0 in a positive way.”

The study’s findings are a call to action for the UK, urging collaboration and the establishment of frameworks to govern AI’s use.

The UK Government, recognising the importance of safe AI implementation, is set to host a global AI Safety Summit at the historic Bletchley Park on 1-2 November 2023. BSI is an official partner for the much-anticipated event.

(Photo by Suad Kamardeen on Unsplash)

See also: UK reveals AI Safety Summit opening day agenda

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post BSI: Closing ‘AI confidence gap’ key to unlocking benefits appeared first on AI News.

The announcement, made by Technology Secretary Michelle Donelan, marks a major step forward in harnessing the potential of AI in revolutionising healthcare. The investment will empower 22 winning projects across universities and NHS trusts, from Edinburgh to Surrey, to drive innovation and transform patient care.

Dr Antonio Espingardeiro, IEEE member and software and robotics expert, comments:

“As it becomes more sophisticated, AI can efficiently conduct tasks traditionally undertaken by humans. The potential for the technology within the medical field is huge—it can analyse vast quantities of information and, when coupled with machine learning, search through records and infer patterns or anomalies in data, that would otherwise take decades for humans to analyse.

We are just starting to see the beginning of a new era where machine learning could bring substantial value and transform the traditional role of the doctor. The true capabilities of this technology as an aide to the healthcare sector are yet to be fully realised. In the future, we may even be able to solve of some of the biggest challenges and issues of our time.

One of the standout projects receiving funding is the University College London’s Centre for Interventional and Surgical Sciences. With a grant exceeding £500,000, researchers aim to develop a semi-autonomous surgical robotics platform designed to enhance the removal of brain tumours. This pioneering technology promises to elevate surgical outcomes, minimise complications, and expedite patient recovery times.

“With the increased adoption of AI and robotics, we will soon be able to deliver the scalability that the healthcare sector needs and establish more proactive care delivery,” added Espingardeiro.

University of Sheffield’s project, backed by £463,000, is focused on a crucial aspect of healthcare – chronic nerve pain. Their innovative approach aims to widen and improve treatments for this condition, which affects one in ten adults over 30.

The University of Oxford’s project, bolstered by £640,000, seeks to expedite research into a foundational AI model for clinical risk prediction. By analysing an individual’s existing health conditions, this AI model could accurately forecast the likelihood of future health problems and revolutionise early intervention strategies.

Meanwhile, Heriot-Watt University in Edinburgh has secured £644,000 to develop a groundbreaking system that offers real-time feedback to trainee surgeons practising laparoscopy procedures, also known as keyhole surgeries. This technology promises to enhance the proficiency of aspiring surgeons and elevate the overall quality of healthcare.

Finally, the University of Surrey’s project – backed by £456,000 – will collaborate closely with radiologists to develop AI capable of enhancing mammogram analysis. By streamlining and improving this critical diagnostic process, AI could contribute to earlier cancer detection.

Ayesha Iqbal, IEEE senior member and engineering trainer at the Advanced Manufacturing Training Centre, said:

“The emergence of AI in healthcare has completely reshaped the way we diagnose, treat, and monitor patients.

Applications of AI in healthcare include finding new links between genetic codes, performing robot-assisted surgeries, improving medical imaging methods, automating administrative tasks, personalising treatment options, producing more accurate diagnoses and treatment plans, enhancing preventive care and quality of life, predicting and tracking the spread of infectious diseases, and helping combat epidemics and pandemics.”

With the UK healthcare sector already witnessing AI applications in improving stroke diagnosis, heart attack risk assessment, and more, the £13 million investment is poised to further accelerate transformative healthcare breakthroughs.

Health and Social Care Secretary Steve Barclay commented:

“AI can help the NHS improve outcomes for patients, with breakthroughs leading to earlier diagnosis, more effective treatments, and faster recovery. It’s already being used in the NHS in a number of areas, from improving diagnosis and treatment for stroke patients to identifying those most at risk of a heart attack.

This funding is yet another boost to help the UK lead the way in healthcare research. It comes on top of the £21 million we recently announced for trusts to roll out the latest AI diagnostic tools and £123 million invested in 86 promising tech through our AI in Health and Care Awards.”

However, the announcement was made the same week as NHS waiting lists hit a record high. Prime Minister Rishi Sunak made reducing waiting lists one of his five key priorities for 2023 on which to hold him “to account directly for whether it is delivered.” Hope is being pinned on technologies like AI to help tackle waiting lists.

This pivotal move is accompanied by the nation’s preparations to host the world’s first major international summit on AI safety, underscoring its commitment to responsible AI development.

Scheduled for later this year, the AI safety summit will provide a platform for international stakeholders to collaboratively address AI’s risks and opportunities.

As Europe’s AI leader, and the third-ranking globally behind the USA and China, the UK is well-positioned to lead these discussions and champion the responsible advancement of AI technology.

(Photo by National Cancer Institute on Unsplash)

See also: BSI publishes guidance to boost trust in AI for healthcare

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post UK commits £13M to cutting-edge AI healthcare research appeared first on AI News.

The guidance, titled ’Validation framework for the use of AI within healthcare – Specification (BS 30440),’ aims to bolster confidence among clinicians, healthcare professionals, and providers regarding the safe, effective, and ethical development of AI tools.

As the global debate on the appropriate use of AI continues, this auditable standard targets products primarily designed for healthcare interventions, diagnoses, and health condition management.

Jeanne Greathouse, Global Healthcare Director at BSI, said:

“This standard is highly relevant to organisations in the healthcare sector and those interacting with it. As AI becomes the norm, it has the potential to be transformative for healthcare.

With the onset of more innovative AI tools, and AI algorithms’ ability to digest and accurately analyse copious amounts of data, clinicians and health providers can efficiently make informed diagnostic decisions to intervene, prevent, and treat diseases, ultimately improving patients’ quality of life.”

According to forecasts, the global healthcare AI market is expected to surpass $187.95 billion by 2030. However, healthcare providers and clinicians may face challenges in assessing AI products due to time and budget constraints or a lack of in-house capabilities. 

The BS 30440 specification seeks to aid decision-making processes by providing criteria for evaluating healthcare AI products, including clinical benefit, performance standards, safe integration into clinical environments, ethical considerations, and equitable social outcomes.

The standard covers a wide range of healthcare AI products, including regulated medical devices like software used for medical purposes, imaging software, patient-facing products like AI-powered smartphone chatbots, and home monitoring devices. It applies to products and technologies utilising AI elements – including machine learning – and is relevant to both AI system suppliers and product auditors.

The development of this specification involved collaboration among a panel of experts, including clinicians, software engineers, AI specialists, ethicists, and healthcare leaders. The guidance draws from existing literature and best practices, translating complex functionality assessments into an auditable framework for AI system conformity.

Healthcare organisations will be able to mandate BS 30440 certification in their procurement processes to ensure adherence to these recognized standards.

Scott Steedman, Director General for Standards at BSI, commented:

“The new guidance can help build digital trust in cutting-edge tools that represent enormous potential benefit to patients, and the professionals diagnosing and treating them.

AI has the potential to shape our future in a positive way and we all need confidence in the tools being developed, especially in healthcare.

This specification, which is auditable, can help guide everyone from doctors to healthcare leaders and patients to choose AI products that are safe, effective, and ethically produced.”

The specification addresses the need for an agreed validation framework for AI development and clinical evaluation in healthcare. It builds on a framework initially piloted at Guy’s and St. Thomas Cancer Centre and later revised through discussions with stakeholders involved in AI and machine learning.

With the publication of this guidance, BSI seeks to instil confidence in AI products used in healthcare and empower doctors, healthcare leaders, and patients to make informed and ethical choices for improved patient care and overall societal benefit.

As AI continues to shape the future of healthcare, adherence to recognised standards will play a vital role in ensuring the safe and effective integration of AI technologies in medical practice.

(Photo by Owen Beard on Unsplash)

See also: AI regulation: A pro-innovation approach – EU vs UK

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post BSI publishes guidance to boost trust in AI for healthcare appeared first on AI News.

The AI Diagnostic Fund will allow NHS Trusts to apply for funding to expedite the deployment of AI imaging and decision support tools, particularly for diagnosing conditions such as cancers, strokes, and heart conditions.

The Health and Social Care Secretary, Steve Barclay, has also pledged to implement AI stroke-diagnosis technology across all stroke networks by the end of 2023, a significant increase from the current 86 percent. This initiative aims to facilitate faster treatment for thousands of stroke patients.

Barclay emphasised the transformative impact of AI on healthcare and its ability to improve patient care and reduce waiting times.

As of April 2023, there were 7.42 million people waiting for treatment on the NHS waiting list in England. This is the highest number of people waiting for treatment since records began in 2004.

Of these patients, nearly 3.09 million were waiting over 18 weeks, and around 371,000 were waiting over a year for treatment. The median waiting time for treatment was 13.8 weeks – almost double the pre-COVID median wait of 7.2 weeks in April 2019.

One of the primary applications of the AI Diagnostic Fund is the use of AI tools for analysing chest X-rays, a common diagnostic tool for lung cancer, which is the leading cause of cancer-related deaths in the UK.

With over 600,000 chest X-rays performed each month in England, the widespread deployment of AI tools to NHS Trusts will aid clinicians in early cancer detection, ultimately improving patient outcomes.

The integration of AI in the NHS has already demonstrated positive results, such as reducing the time it takes to diagnose and treat stroke victims. By enabling faster stroke diagnosis, AI has been shown to triple the chances of patients living independently after a stroke.

Sridhar Iyengar, Managing Director of Zoho Europe, said:

“Artificial Intelligence is set to play a crucial role in the future of many industries, including digital healthcare. It could enable doctors and nurses to make faster, more accurate decisions.

Key to its continued success is building trust with the public, ensuring the highest standards of data management, to protect the privacy of patients.

Deployed correctly, AI can save time and money. This is something that is already seen in many private sector businesses across the UK and public services can benefit from following suit.”

The funding provided through the AI Diagnostic Fund will be available to support the implementation of any AI diagnostic tool that NHS Trusts wish to deploy. However, the proposals must demonstrate value for money to receive approval.

The government has already invested £123 million in 86 AI technologies, benefiting patients through improved stroke diagnosis, screening, cardiovascular monitoring, and home-based condition management.

The introduction of AI into healthcare aligns with the NHS’s mission to adopt the latest proven technology to enhance patient care and provide value for taxpayers.

Dr Katharine Halliday, President of the Royal College of Radiologists, said:

“At a time when diagnostic services are under strain, it is critical that we embrace innovation that could boost capacity – and so we welcome the Government’s announcement of a £21 million fund to purchase and deploy AI diagnostic tools.

All doctors want to give patients the best possible care. This starts with a timely diagnosis, and crucially, catching diseases at the earliest point. There is huge promise in AI, which could save clinicians time by maximising our efficiency, supporting our decision-making and helping identify and prioritise the most urgent cases.

Together with a highly trained and expert radiologist workforce, AI will undoubtedly play a significant part in the future of diagnostics.”

To ensure the safe deployment of AI devices, the government recently established the AI & Digital Regulation Service, which assists NHS staff in accessing the necessary information and guidance. This service simplifies the understanding of AI regulations in the NHS, enabling developers and adopters of AI to bring their products to market more efficiently.

The investment in AI technology is crucial, considering that the NHS currently spends £10 billion annually on medical technology, and the global market is projected to reach £150 billion next year. Access to innovative technologies promises significant benefits for patients, including disease prevention, early diagnosis, effective treatments, and faster recovery.

Dr Antonio Espingardeiro, IEEE member, software and robotics expert, commented:

“As it becomes more sophisticated, AI can efficiently conduct tasks traditionally undertaken by humans, the potential for the technology within the medical field is huge. It can analyse vast quantities of information, and when coupled with machine learning, search through records and infer patterns or anomalies in data, that would otherwise take decades for humans to analyse.

We are just starting to see the beginning of a new era where machine learning could bring substantial value and transform the traditional role of the doctor. The true capabilities of this technology as an aide to the healthcare sector are yet to be fully realised.

In the future, we may even be able to solve of some of the biggest challenges and issues of our time. With the increased adoption of AI and robotics, we will soon be able to deliver the scalability that the healthcare sector needs and establish more proactive care delivery.”

With the support of AI, NHS staff can look forward to enhanced capabilities in diagnosing and treating patients, leading to improved healthcare outcomes and a more efficient healthcare system overall.

(Photo by Ian Taylor on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.

The post NHS receives AI fund to improve healthcare efficiency appeared first on AI News.

The National Institute for Health and Care Research (NIHR) is contributing more than £1 million in funding to develop the new technology, which is known as Organ Quality Assessment (OrQA). It works in the same way as Artificial Intelligence-based facial recognition to evaluate the quality of an organ.

It is estimated the technology could result in up to 200 more patients receiving kidney transplants and 100 more receiving liver transplants a year in the UK.

Colin Wilson, transplant surgeon at Newcastle upon Tyne Hospitals NHS Foundation Trust and co-lead of the project, said: “Transplantation is the best treatment for patients with organ failure, but unfortunately some organs can’t be used due to concerns they won’t function properly once transplanted.

“The software we have developed ‘scores’ the quality of the organ and aims to support surgeons to assess if the organ is healthy enough to be transplanted.

“Our ultimate hope is that OrQA will result in more patients receiving life-saving transplants and enable them to lead healthier, longer lives.”

Professor Hassan Ugail, director of the Centre for Visual Computing at the University of Bradford, whose team is working on image analysis as part of the research, said: “Currently, when an organ becomes available, it is assessed by a surgical team by sight, which means, occasionally, organs will be deemed not suitable for transplant.

“We are developing a deep machine learning algorithm which will be trained using thousands of images of human organs to assess images of donor organs more effectively than what the human eye can see.

“This will ultimately mean a surgeon could take a photo of the donated organ, upload it to OrQA and get an immediate answer as to how best to use the donated organ.”

There are currently nearly 7,000 patients awaiting organ transplant in the UK. An organ can only survive out of the body for a limited time. In most cases, only one journey from the donor hospital to the recipient hospital is possible. This means it is essential that the right decision is made quickly.

The project is being supported by NHS Blood and Transplant (NHSBT), Quality in Organ Donation biobank and an NIHR Blood and Transplant Research Unit to deliver research for the NHS. It also involves academics from the Universities of Oxford and New South Wales.?

Professor Derek Manas, medical director of NHSBT Organ Donation and Transplantation, said: “This is an exciting development in technological infrastructure that, once validated, will enable surgeons and transplant clinicians to make more informed decisions about organ usage and help to close the gap between those patients waiting for and those receiving lifesaving organs. We at NHSBT are extremely committed to making this exciting venture a success.”

Health Minister Neil O’Brien said: “Technology has the ability to revolutionise the way we care for people and this cutting edge technology will improve organ transplant services. Developed here in the UK, this pioneering new method could save hundreds of lives and ensure the best use of donated organs.

“I encourage everyone to register their organ donation decision. Share it with your family so your loved ones can follow your wishes and hopefully save others.”

Chief executive of the NIHR Professor, Lucy Chappell, said: “Funded by our Invention for Innovation Programme, this deep machine learning algorithm aims to increase the number of liver and kidney donor organs suitable for transplantation. This is another example of how AI can enhance our healthcare system and make it more efficient. Once clinically validated and tested, cutting edge technology such as this holds the real promise of saving and improving lives.”

‘Proof of concept’ work has been carried out in liver, kidney and pancreas transplantation as well as at an advanced stage of pre-clinical testing in liver and kidney.

It is hoped the OrQA software will be ready for a licensing study within the NHS within two years. There is also the possibility of marketing the tool worldwide.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post AI being used to cherry-pick organs for transplant appeared first on AI News.

Brits have become used to long NHS wait times for many years. However, the post-covid backlog has sent the number of patients on waiting lists rocketing:

There are many strong views on what NHS reforms are needed, but one thing everyone can agree on is that the current trajectory is unsustainable. Modern technologies will be vital in delivering the improvements that will help both NHS staff and patients.

The Walton Centre NHS Foundation Trust has announced a partnership with TCS to develop digital solutions that increase the productivity of specialists, reduce waiting times for patients, and improve the overall experience. 

Shalini Mathur, Business Unit Head of Public Services for the UK, Europe, and ANZ at TCS, said:

“We are pleased to partner with The Walton Centre to transform patient care in the UK using next-gen technologies.

These technologies and solutions will help reduce waiting times for patients while improving the productivity of specialist consultants. This creates a blueprint for similar digital innovation in other clinical settings.”

The first product of this partnership is an AI chatbot that aims to transform how patients with headaches are diagnosed and treated.

A headache can range from nothing serious to being potentially fatal or life-changing. Anyone who is concerned their headache could be out-of-the-ordinary should get it checked out, but deciding which patients should be prioritised is a critical but difficult task.

Patients with headaches make up the largest number of outpatient referrals to neurologists at The Walton Centre. The use of a chatbot will enable information about the patient’s condition to be collected in order to compile a detailed report for clinicians to review before an initial appointment.

Dependent on the clinician’s assessment, a patient may be put on a fast track for an examination or offered guidance on alleviating symptoms while they wait for their turn.

Dr Anita Krishnan, Divisional Clinical Director for Neurology at The Walton Centre, and a Consultant Neurologist specialising in headaches, commented:

“Technology is a huge part of medicine and it’s exciting to work with TCS to create a new artificial intelligence-based solution which will help our patients.

The chatbot system also has the potential to be extended into other areas of medicine, which could benefit even more patients.

We are working closely with TCS and our other specialist partners to ensure the new solution is effective and safe and improves efficiency and patient outcomes.”

While it’s a fairly limited trial to begin with, AI-powered chatbots could make a real difference across the NHS. Chatbots can help to ensure that patients are correctly prioritised and less of the scarce time consultants have available is spent having to ask the questions for information that can be collected beforehand.

Chatbots aren’t going to solve all of the NHS’ problems, but they should make a positive difference for staff and patients.

(Photo by Nicolas J Leclercq on Unsplash)

The post The NHS hopes an AI chatbot will help tackle patient wait times appeared first on AI News.

Nuance became a household name for creating the speech engine recognition engine behind Siri. In recent years, the company has put a strong focus on AI solutions for healthcare and is now a full-service partner of 77 percent of US hospitals and is trusted by over 500,000 physicians daily.

Earlier this year, Microsoft acquired Nuance with the promise of ushering in a “new era of outcomes-based AI”. Microsoft is also active in the healthcare space and its acquisition of Nuance was investigated by regulators over concerns it may reduce competition.

Regulators ultimately ended up giving the deal the thumbs up.

The EU’s regulator, for example, concluded that Nuance would continue to face stiff competition in the future, the data Microsoft gains would not provide it with an advantage to shut out competitors, and there’d be no ability/incentive to foreclose existing solutions.

“Combining the power of Nuance’s deep vertical expertise and proven business outcomes across healthcare, financial services, retail, telecommunications, and other industries with Microsoft’s global cloud ecosystems will enable us to accelerate our innovation and deploy our solutions more quickly, more seamlessly, and at greater scale to solve our customers’ most pressing challenges,” said Mark Benjamin, CEO of Nuance, at the time of Microsoft’s acquisition.

Nuance says both companies represent two of the most trusted and innovative technology organisations in the world. As such, it believes Nuance and Microsoft are in a position to foster a community anchored in collaboration with key leading health systems (LHS) executives and experts across the healthcare ecosystem. That community will be The AI Collaborative.

“Our members have expressed their desire for a dedicated space to explore AI in healthcare and its enormous potential to improve outcomes and clinical workflow,” said Renee DeSilva, CEO of The Academy.

“We are thrilled to expand our partnership with Microsoft and Nuance to introduce The AI Collaborative, a new program at The Academy designed exclusively for clinical and operational executives who lead their organization’s approach to investing in AI as a strategic initiative.”

The AI Collaborative will bring together senior leaders from LHS to understand their current and future needs and create the AI and ML innovations required to fulfil them.

“The key to successful healthcare innovation using AI is understanding at a deep level the problems that you’re trying to solve and focusing on the outcomes you want to achieve,” explained Peter Durlach, Chief Strategy Officer of Nuance.

“With the combined engineering, market and domain expertise of Nuance and Microsoft, The AI Collaborative can bring together multiple technical, business and clinical stakeholders to prioritize deployment of solutions for clinician burnout, patient engagement and health system financial stability, while accelerating innovation in precision medicine, drug discovery, clinical decision support and other promising use cases across the entire healthcare ecosystem.”

The AI Collaborative will commence in September 2022 and kick off with a visit to Microsoft’s corporate HQ. Annual summits will be held going forward where stakeholders will learn how to best utilise patient-specific data and insights to augment care delivery, reduce care variation, and support operational improvements.

(Photo by Cytonn Photography on Unsplash)

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

The post Nuance partners with The Academy to launch The AI Collaborative appeared first on AI News.