AI

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„Swarm Learning“

AI with swarm intelligence to analyse medical data

Communities benefit from sharing knowledge and experience among their members. Following a similar principle - called “swarm learning” - an international research team has trained artificial intelligence algorithms to detect blood cancer, lung diseases and Covid-19 in data stored in a decentralized fashion. This approach has advantage over conventional methods since it inherently provides…

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Combining common risk factors

Deep learning enables dual screening for cancer and CVD

Heart disease and cancer are the leading causes of death in the United States, and it’s increasingly understood that they share common risk factors, including tobacco use, diet, blood pressure, and obesity. Thus, a diagnostic tool that could screen for cardiovascular disease while a patient is already being screened for cancer has the potential to expedite a diagnosis, accelerate treatment, and…

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AI-as-a-service

Carestream accelerates development and delivery of AI applications for medical imaging

Carestream Health is transforming and accelerating the way it develops and delivers AI applications for medical imaging that help improve patient care. The state-of-the-art initiative is based on Hewlett Packard Enterprise’s (HPE) GreenLake for Machine Learning Operations (ML Ops). The machine-learning-optimized cloud service infrastructure makes it easier and faster to get started with ML/AI…

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Digital pathology

Today’s tissue for tomorrow’s research

Specialist biorepositories are helping advance personalised medicine by supporting the availability of human tissue for research using digital pathology techniques. The pivotal role of the Glasgow Tissue Research Facility (GTRF) in making tissue available to shape new therapies and treatments was outlined in a presentation to the online “Transforming Digital Pathology – Integrating AI to Move…

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Intelligent health

Introducing AI across the NHS

Artificial Intelligence in health and care is being introduced across the UK via a major national project that is already producing a range of innovations. Latest developments were outlined to the online Intelligent Health conference in a headlining presentation by Dr Indra Joshi, Director of AI at NHSX, which is a joint unit bringing together teams from NHS England and NHS Improvement, and the…

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AI in cardiology

Machine learning accurately predicts cardiac arrest risk

A branch of artificial intelligence (AI), called machine learning, can accurately predict the risk of an out of hospital cardiac arrest--when the heart suddenly stops beating--using a combination of timing and weather data, finds research published online in the journal Heart. Machine learning is the study of computer algorithms, and based on the idea that systems can learn from data and identify…

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AI-based technology

Image improvement with smart noise cancellation

Carestream Health has released Smart Noise Cancellation (SNC), a groundbreaking artificial intelligence (AI)-based technology that greatly improves image quality — producing images that are significantly clearer than with standard processing.

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Intensive care support

AI predicts daily ICU trajectory for critical Covid-19 patients

Researchers used AI to identify which daily changing clinical parameters best predict intervention responses in critically ill Covid-19 patients. The investigators used machine learning to predict which patients might get worse and not respond positively to being turned onto their front in intensive care units (ICUs) - a technique known as proning that is commonly used in this setting to improve…

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LVAD patients monitoring

5G and AI: Telemedicine support for chronic heart failure patients

A new research project will embrace the combination of 5G telecommunications technology and AI to offer continuous remote monitoring to seriously ill heart failure patients. An increasing number of chronic heart failure patients are receiving Left Ventricular Assist Devices (LVADs) to help them live with their condition, but physicians acknowledge the need to effectively monitor them.

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Innovation in intervention

The promise and reality about AI for interventional oncology

Is artificial intelligence (AI) technology ready to be utilized as a clinical tool by interventional oncologists? Not yet, but when it is, AI technology’s clinical impact may be as profound as advanced imaging is today. This is the consensus of two leading researchers developing AI for interventional oncology use, who presented back-to-back scientific sessions at ECIO 2021 on both the promise…

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More targeted treatment

AI could improve outcomes for bowel cancer patients

A test which uses artificial intelligence (AI) to measure proteins present in some patients with advanced bowel cancer could hold the key to more targeted treatment, according to new research. A team at the University of Leeds collaborated with researchers at Roche Diagnostics to develop the technique, which will help doctors and patients to decide on the best treatment options.

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Merging modalities

AI combines ECG and X-ray to diagnose arrhythmic disorders

Kobe University Hospital’s Dr. Makoto Nishimori and Project Assistant Professor Kunihiko Kiuchi et al. (of the Division of Cardiovascular Medicine, Department of Internal Medicine) have developed an AI that uses multiple kinds of test data to predict the location of surplus pathways in the heart called ‘accessory pathways’, which cause the heart to beat irregularly. In this study, the…

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Incidental findings identification

AI system for brain MRIs could boost workflows

An artificial intelligence (AI)-driven system that automatically combs through brain MRIs for abnormalities could speed care to those who need it most, according to a new study. “There are an increasing number of MRIs that are performed, not only in the hospital but also for outpatients, so there is a real need to improve radiology workflow,” said study co-lead author Romane Gauriau, PhD,…

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Discerning good algorithms from bad ones

Medical AI evaluation is surprisingly patchy, study finds

In just the last two years, artificial intelligence has become embedded in scores of medical devices that offer advice to ER doctors, cardiologists, oncologists, and countless other health care providers. But how much do either regulators or doctors really know about the accuracy of these tools? A new study led by researchers at Stanford, some of whom are themselves developing devices, suggests…

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Outcome prediction

Deep learning to maximize lifespan after liver transplant

Researchers from the Canadian University Healh Network (UHN) have developed and validated a deep learning model to predict a patient's long-term outcome after receiving a liver transplant. First of its kind in the field of Transplantation, this model is the result of a collaboration between the Ajmera Transplant Centre and Peter Munk Cardiac Centre (PMCC). The study, published in Lancet Digital…

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Shepherding medical data

Machine learning platform turns healthcare data into insights

Over the past decade, hospitals and other healthcare providers have put massive amounts of time and energy into adopting electronic healthcare records, turning hastily scribbled doctors' notes into durable sources of information. But collecting these data is less than half the battle. It can take even more time and effort to turn these records into actual insights — ones that use the learnings…

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'GI Genius'

FDA authorizes marketing of first AI device to help colon cancer early detection

The U.S. Food and Drug Administration authorized marketing of the GI Genius, the first device that uses artificial intelligence (AI) based on machine learning to assist clinicians in detecting lesions (such as polyps or suspected tumors) in the colon in real time during a colonoscopy. “Artificial intelligence has the potential to transform health care to better assist health care providers and…

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Diagnostics team-up

Cooperation to accelerate adoption of AI-powered digital pathology

Royal Philips and Ibex Medical Analytics announced a strategic collaboration to jointly promote their digital pathology and AI solutions to hospitals, health networks and pathology labs worldwide. The combination of Philips digital pathology solution (Philips IntelliSite Pathology Solution) and Ibex’s Galen AI-powered cancer diagnostics platform, currently in clinical use in Europe and the…

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Surgical robotics

Elevating outcomes of surgery

What’s in a name? In the case of Asensus Surgical, Inc., previously known as TransEnterix, Inc., the recent rebranding doubles as a mission statement for the manufacturer of surgical robotics systems: The initial ‘A’ stands for artificial intelligence and augmented surgery, reflecting the company’s emphasis on new technologies designed to enhance the operator’s cognition (‘sensus’…

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Mammography support

AI solution may reduce interval breast cancer rates

Medical technology company iCAD, Inc. announced that ProFound AI for 2D Mammography might notably reduce the risk of interval breast cancer, according to a new retrospective analysis. The aim of the study was to determine if adding AI to reading mammography as a supportive tool may help in decreasing the interval cancer rate in population-based organized mammography screening programs in Germany.

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Digital pathology

AI delivers cervical cancer screening to rural areas of Kenya

Experts from Sweden, Finland and Kenya are using digital microscopy combined with Artificial Intelligence (AI) to deliver a rapid and effective cervical screening service to rural locations in Kenya. The project sees AI and digital diagnostics bridge the gap between low-resource settings and the availability of centralised AI-enhanced expertise and pathology services, located in larger cities in…

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HPV testing advances

Cervical cancer screening: Emerging tech to replace Pap smears

Emerging technologies can screen for cervical cancer better than Pap smears and, if widely used, could save lives both in developing nations and parts of countries, like the United States, where access to health care may be limited. In Biophysics Reviews, by AIP Publishing, scientists at Massachusetts General Hospital write advances in nanotechnology and computer learning are among the…

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