Machine learning

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DRUML

New AI offers hope for deadly liver cancer patients

Researchers at King's College Hospital and Queen Mary University of London have shown that a new computer-based algorithm can rank drugs used to treat primary liver cancer, based on their efficacy in…

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Pregnancy imaging

Machine learning predicts placenta health from MRI scans

Machine learning methods are being used to predict the health of the placenta from a 30-second MRI scan. Researchers hope the approach will offer an insight into the health of expectant mothers and…

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Blood clots in the legs

Machine learning algorithm to diagnose deep vein thrombosis

A team of researchers are developing the use of an artificial intelligence (AI) algorithm with the aim of diagnosing deep vein thrombosis (DVT) more quickly and as effectively as traditional…

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Biological image analysis

Machine learning accelerates super-resolution microscopy

Scientists use super-resolution microscopy to study previously undiscovered cellular worlds, revealing nanometer-scale details inside cells. This method revolutionized light microscopy and earned its…

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Diagnosis, prognosis, prediction

AI offers advances in cardiovascular imaging

Artificial Intelligence (AI) is providing numerous opportunities across clinical care in the field of cardiovascular imaging. While challenges remain, AI is being applied in terms of diagnosis and…

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Cardiology & AI

Machine learning to predict sudden cardiac death

Could machine learning (ML) help to predict sudden cardiac death (SCD)? According to Dr Sanjiv Narayan, Professor of Medicine at Stanford University, California, many exciting studies are using ML to…

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Identificación de mutaciones tumorales

El aprendizaje automático impulsa la medicina personalizada del cáncer

El laboratorio de Genómica Biomédica del IRB Barcelona (Institute for Research in Biomedicine) ha desarrollado un método computacional que identifica las mutaciones causantes del cáncer para cada tipo de tumor. Este y otros desarrollos del mismo laboratorio buscan acelerar la investigación oncológica y ofrecer herramientas para que los oncólogos puedan elegir el mejor tratamiento para cada…

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Tool to identify tumour mutations

Machine learning fuels personalised cancer medicine

The Biomedical Genomics laboratory at the Institute for Research in Biomedicine (IRB) Barcelona has developed a computational tool that identifies cancer driver mutations for each tumour type. This and other developments produced by the same lab seek to accelerate cancer research and provide tools to help oncologists choose the best treatment for each patient. The study has been published in the…

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Intensive care & AI

Machine learning model predicts ICU patients' mortality risk

A research team at Universitat Autònoma de Barcelona (UAB), in collaboration with the Hospital de Mataró, developed a new machine learning-based model that predicts the risk of mortality of intensive care unit patients according to their characteristics. The research was published in the latest edition of the journal Artificial Intelligence in Medicine, with a special mention as a…

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Connectome analysis

Machine learning improves prediction of stroke recovery

An international team of scientists led by EPFL has developed a system that combines information from the brain’s connectome – the “wiring” between neurons – and machine learning to assess and predict the outcome of stroke victims. When blood flow to the brain is somehow reduced or restricted, a person can suffer what we know as a stroke (from “ischemic stroke” in medical jargon).…

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WHO global report

The six guiding principles for AI in healthcare

Artificial Intelligence (AI) holds great promise for improving the delivery of healthcare and medicine worldwide, but only if ethics and human rights are put at the heart of its design, deployment, and use, according to new WHO guidance. The report, Ethics and governance of artificial intelligence for health, is the result of 2 years of consultations held by a panel of international experts…

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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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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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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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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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Model analysis

Machine learning for Covid-19 diagnosis: promising, but still too flawed

Systematic review finds that machine learning models for detecting and diagnosing Covid-19 from medical images have major flaws and biases, making them unsuitable for use in patients. However, researchers have suggested ways to remedy the problem. Researchers have found that out of the more than 300 Covid-19 machine learning models described in scientific papers in 2020, none of them is suitable…

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"Alexa, do I have an irregular heart rhythm?"

AI uses smart speakers for contactless cardiac monitoring

Smart speakers, such as Amazon Echo and Google Home, have proven adept at monitoring certain health care issues at home. For example, researchers at the University of Washington have shown that these devices can detect cardiac arrests or monitor babies breathing. But what about tracking something even smaller: the minute motion of individual heartbeats in a person sitting in front of a smart…

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Potential for rapid, accurate glycan sequencing

Enormous boost for sequencing key molecules

Using a nanopore, researchers have demonstrated the potential to reduce the time required for sequencing a glycosaminoglycan — a class of long chain-linked sugar molecules as important to our biology as DNA — from years to minutes. Research to be published this week in the Proceedings of the National Academies of Sciences shows that machine-learning and image recognition software could be…

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Survival prediction

Deep learning may lead to better lung cancer treatments

Doctors and healthcare workers may one day use a machine learning model, called deep learning, to guide their treatment decisions for lung cancer patients, according to a team of Penn State Great Valley researchers. In a study, the researchers report that they developed a deep learning model that, in certain conditions, was more than 71% accurate in predicting survival expectancy of lung cancer…

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AI 'Haven' in intensive care

Machine learning to identify deteriorating hospital patients

Researchers in Oxford have developed a machine learning algorithm that could significantly improve clinicians’ ability to identify hospitalised patients whose condition is deteriorating to the extent that they need intensive care. The HAVEN system (Hospital-wide Alerting Via Electronic Noticeboard) was developed as part of a collaboration between the University of Oxford’s Institute of…

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Detecting depression, psychosis

Machine learning could aid mental health diagnoses

A way of using machine learning to more accurately identify patients with a mix of psychotic and depressive symptoms has been developed by researchers at the University of Birmingham. Patients with depression or psychosis rarely experience symptoms of purely one or the other illness. Historically, this has meant that mental health clinicians give a diagnosis of a ‘primary’ illness, but with…

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Image-based diagnosis of Covid-19

AI detects coronavirus on CT scans

In order to detect the Corona virus SARS-CoV-2, there are further methods of diagnosis apart from the globally used PCR tests (Polymerase chain reaction): The infection can also be recognised on CT scans – for which Artificial Intelligence (AI) can be used as well. An AI system can not only filter CT scan of Covid-19 patients from a data set, but also estimate, which areas of the image are of…

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