Machine Learning News and Research

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AI can detect signs of lung-clogging blot clots in electrocardiograms, shows study

Pulmonary embolisms are dangerous, lung-clogging blot clots. In a pilot study, scientists at the Icahn School of Medicine at Mount Sinai showed for the first time that artificial intelligence (AI) algorithms can detect signs of these clots in electrocardiograms (EKGs), a finding which may one day help doctors with screening.

22 Dec 2021

Researchers use machine learning to shed light on genetic mutations linked with spina bifida

Weill Cornell Medicine researchers are using machine learning, a form of artificial intelligence, to shed light on genetic mutations associated with spina bifida.

20 Dec 2021

New tool provides an unprecedented view of brain cell activity in a synapse

To solve the mysteries of how learning and memory occur, Johns Hopkins Medicine scientists have created a system to track millions of connections among brain cells in mice — all at the same time — when the animals' whiskers are tweaked, an indicator for learning.

20 Dec 2021

Study employs computer algorithms to understand doctor-patient communication

A computer analysis of hundreds of thousands of secure email messages between doctors and patients found that most doctors use language that is too complex for their patients to understand.

18 Dec 2021

Identifying protein targets in SARS-CoV-2 via machine learning

A new study provides insight on using an ML-based algorithm to analyze and predict therapeutic targets in emerging pathogens with a range of mutations.

17 Dec 2021

Extensive dataset may help develop deeper insights in cognitive and computational neuroscience

Researchers from the University of Minnesota Medical School have published an extensive dataset that uses cutting-edge, high-field (7T) fMRI technology to probe how humans perceive, interpret and memorize naturalistic photographs.

16 Dec 2021

Novel technique developed to observe cancer cells’ metastatic potential

When cancer cells metastasize, they morph, becoming missile-shaped in order to penetrate into other tissues throughout the body.

16 Dec 2021

New review examines the advances and future trends in sleep disorder measurement technology

Sleep disorders and insufficient sleep are major global problems contributing to, e.g., increased health care costs and sick leaves, and reduced quality of life. According to recent estimates, sleep apnea alone affects approximately 1 billion people worldwide, and up to half of the world’s population suffers from insomnia at some point in their lives.

16 Dec 2021

Scientists to explore the ‘cognobiome’ of soldiers using Microba’s analysis platform

Leading Australian universities will explore the ‘cognobiome’ of soldiers using Microba Life Science’s analysis platform to discover opportunities for improving cognitive and physiological performance.

16 Dec 2021

UB researchers analyze pandemic-related shifts in alcohol sales across 16 U.S. states

An analysis of data from 16 U.S. states suggests that the first few months of the COVID-19 pandemic saw increases in wine and spirit sales, accompanied by notable changes in the relationship between alcohol sales and people's visits to businesses that sell alcohol.

15 Dec 2021

SARS-CoV-2 Omicron variant binding to its receptor and therapeutic entities

Researchers generated a set of computed structural models of the Omicron receptor-binding domain attached to its receptor angiotensin-converting enzyme.

15 Dec 2021

BrainGlobe; An Open-Source Platform for Neuroscientists

An interview with Professor Troy Margrie, Associate Director of the Sainsbury Wellcome Centre, and Dr. Adam Tyson, Scientific Software Lead at the Institute of Cancer Research.

15 Dec 2021

Machine learning method for determining impact of mutations in the SARS-CoV-2 RBD on binding and antibody escape

Deep mutational learning (DML) is a technique developed by researchers from multiple institutions that combines experimental yeast display screening of RBD mutagenesis libraries with deep sequencing and machine learning.

14 Dec 2021

Digital interventions may help meet the growing demand for psychological treatment

The COVID-19 pandemic has had a major impact on mental health across the globe. Depression is predicted to be the leading cause of lost life years due to illness by 2030.

13 Dec 2021

Novel AI score predicts risk of death in patients with suspected or known coronary artery disease

A novel artificial intelligence score provides a more accurate forecast of the likelihood of patients with suspected or known coronary artery disease dying within 10 years than established scores used by health professionals worldwide.

11 Dec 2021

Machine-learning model could help identify treatments that pose higher risk than other options

Sepsis claims the lives of nearly 270,000 people in the U.S. each year. The unpredictable medical condition can progress rapidly, leading to a swift drop in blood pressure, tissue damage, multiple organ failure, and death.

11 Dec 2021

iVention joins the Tetra Partner Network to meet customer demand for data-engineered scientific workflows

TetraScience, the R&D Data Cloud company, announced today that iVention, maker of a powerful Laboratory Execution System, has joined the Tetra Partner Network to meet customer requirements that all of their scientific data be engineered, liquid, and actionable so that they can accelerate delivery of life-saving medicines.

From TetraScience, Inc. 8 Dec 2021

Study analyzes the contribution of AI to cancer patient care and vaccine design

Artificial Intelligence/Machine Learning (AI/ML) is the development of computer systems that are able to perform tasks that would normally require human intelligence. AI/ML is used by people every day, for example, while using smart home devices or digital voice assistants.

8 Dec 2021

AI-based technology to identify patients at risk of serious illness as a result of blood infections

A new technology developed at Tel Aviv University will make it possible, using artificial intelligence, to identify patients who are at risk of serious illness as a result of blood infections.

8 Dec 2021

Novel AI-based system models the progression of chronic diseases as patients age

Using artificial intelligence, a team of University at Buffalo researchers has developed a novel system that models the progression of chronic diseases as patients age.

7 Dec 2021

Machine Learning News and Research

AI can detect signs of lung-clogging blot clots in electrocardiograms, shows study

Researchers use machine learning to shed light on genetic mutations linked with spina bifida

New tool provides an unprecedented view of brain cell activity in a synapse

Study employs computer algorithms to understand doctor-patient communication

Identifying protein targets in SARS-CoV-2 via machine learning

Extensive dataset may help develop deeper insights in cognitive and computational neuroscience

Novel technique developed to observe cancer cells’ metastatic potential

New review examines the advances and future trends in sleep disorder measurement technology

Scientists to explore the ‘cognobiome’ of soldiers using Microba’s analysis platform

UB researchers analyze pandemic-related shifts in alcohol sales across 16 U.S. states

SARS-CoV-2 Omicron variant binding to its receptor and therapeutic entities

BrainGlobe; An Open-Source Platform for Neuroscientists

Machine learning method for determining impact of mutations in the SARS-CoV-2 RBD on binding and antibody escape

Digital interventions may help meet the growing demand for psychological treatment

Novel AI score predicts risk of death in patients with suspected or known coronary artery disease

Machine-learning model could help identify treatments that pose higher risk than other options

iVention joins the Tetra Partner Network to meet customer demand for data-engineered scientific workflows

Study analyzes the contribution of AI to cancer patient care and vaccine design

AI-based technology to identify patients at risk of serious illness as a result of blood infections

Novel AI-based system models the progression of chronic diseases as patients age

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