Machine Learning News and Research

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Machine-learning algorithm helps sort out huge amounts of data for protein research

Sorting huge amounts of data is a bottleneck in protein research, a field that is crucial to make use of the gene-editing technology CRISPR and fully understand diseases like cancer, Alzheimer's and Parkinson's

3 Nov 2020

NUS researchers develop high sensitivity, low hysteresis pressure sensor

Real-time health monitoring and sensing abilities of robots require soft electronics, but a challenge of using such materials lie in their reliability.

2 Nov 2020

Machine learning increases the accuracy of anti-cancer drug response predictions

With the advent of pharmacogenomics, machine learning research is well underway to predict the patients' drug response that varies by individual from the algorithms derived from previously collected data on drug responses.

2 Nov 2020

New model aims to predict risk of cardiovascular disease in people with type 2 diabetes

Researchers from the University of Sydney’s School of Project Management within the Faculty of Engineering have developed a model which aims to predict the risk of people living with type 2 diabetes developing cardiovascular disease.

2 Nov 2020

Study finds irritated skin as strongest predictor of hospital-acquired pressure injury

Nursing assessments of patients' skin conditions may seem routine, but an analysis of more than 5,000 patient records underscores the importance of treating and monitoring irritated skin early and eliminating the cause as an important step to prevent pressure injuries.

2 Nov 2020

RNI researchers to study the impact of excessive speeds on the human brain, body

Before the first Virgin Hyperloop ride takes off, the brains behind pioneering neuroscience research at West Virginia University will help ensure the health and well-being of its passengers and operators.

30 Oct 2020

New machine learning-based approach helps detect atrial fibrillation drivers

Researchers from Skoltech and their US colleagues have designed a new machine learning-based approach for detecting atrial fibrillation drivers, small patches of the heart muscle that are hypothesized to cause this most common type of cardiac arrhythmia.

29 Oct 2020

Novel device can benefit patients with upper limb paralysis

A tiny device the size of a small paperclip has been shown to help patients with upper limb paralysis to text, email and even shop online in the first human trial.

29 Oct 2020

Brain-computer interface enables patients with severe paralysis to resume daily tasks

Researchers demonstrated the success of a fully implantable wireless medical device, the Stentrode™ brain-computer interface (BCI), designed to allow patients with severe paralysis to resume daily tasks -- including texting, emailing, shopping and banking online -- without the need for open brain surgery.

28 Oct 2020

Physical stress caused by interruptions in workplace

ETH researchers have used an experiment in a simulated group office environment to show for the first time that the body produces more stress hormones when people are repeatedly interrupted at work.

28 Oct 2020

Deep learning models help hunt for COVID-19 drugs

Michigan State University Foundation Professor Guowei Wei wasn't preparing machine learning techniques for a global health crisis. Still, when one broke out, he and his team were ready to help.

28 Oct 2020

Novel machine learning algorithm helps find drug binding sites

Scientists from the iMolecule group at Skoltech Center for Computational and Data-Intensive Science and Engineering developed BiteNet, a machine learning algorithm that helps find drug binding sites, i.e. potential drug targets, in proteins.

27 Oct 2020

Researchers investigate how brain signaling gives rise to decision-making

Increasingly, biologists are turning to computational modeling to make sense of complex systems. In neuroscience, researchers are adapting the kinds of algorithms used to forecast the weather or filter spam from your email to seek insight into how the brain's neural networks process information.

27 Oct 2020

New tool predicts prognosis of individual patients with COVID-19

A new artificial intelligence-based score considers multiple factors to predict the prognosis of individual patients with COVID-19 seen at urgent care clinics or emergency departments.

27 Oct 2020

Researchers identify molecular processes in kidney cells that attract and feed COVID-19

Although the lungs are a common target for COVID-19's cytokine storm, so are the kidneys, making the 1 in 4 U.S. adults with diabetes resulting in diabetic kidney disease at increased risk for virus mortality.

23 Oct 2020

Molecular processes in kidney cells may increase diabetics' vulnerability to COVID-19 infection

People with diabetes -- especially the 20 to 40 percent with diabetic kidney disease -- are among the most at risk for serious complications and death from COVID-19.

23 Oct 2020

Researchers propose using complexity science to respond better to the COVID-19 pandemic

The COVID-19 pandemic has fundamentally disrupted U.S. healthcare organizations. Hospitals have faced drug and device shortages and created new ICUs overnight. Care plans have evolved out of necessity, and hospitals' carefully constructed patient flow systems were up-ended.

23 Oct 2020

Novel tool can provide rapid stroke diagnosis from interaction with a smartphone

A new tool created by researchers at Penn State and Houston Methodist Hospital could diagnose a stroke based on abnormalities in a patient's speech ability and facial muscular movements, and with the accuracy of an emergency room physician -- all within minutes from an interaction with a smartphone.

22 Oct 2020

Researchers successfully perform terahertz imaging of early-stage breast cancer without staining

A team of researchers at Osaka University, in collaboration with the University of Bordeaux and the Bergonié Institute in France, has succeeded in terahertz imaging of early-stage breast cancer less than 0.5 mm without staining, which is difficult to identify even by pathological diagnosis.

21 Oct 2020

Brain imaging biomarker may help predict treatment response in patients with psychiatric disorders, study reveals

Cohen Veterans Bioscience, a non-profit research biotech advancing brain health solutions, today announces findings from a study which generates new evidence in support of a critical brain imaging biomarker, that may help guide people who suffer from post-traumatic stress disorder or major depressive disorder towards the most effective treatment.

21 Oct 2020

Machine Learning News and Research

Machine-learning algorithm helps sort out huge amounts of data for protein research

NUS researchers develop high sensitivity, low hysteresis pressure sensor

Machine learning increases the accuracy of anti-cancer drug response predictions

New model aims to predict risk of cardiovascular disease in people with type 2 diabetes

Study finds irritated skin as strongest predictor of hospital-acquired pressure injury

RNI researchers to study the impact of excessive speeds on the human brain, body

New machine learning-based approach helps detect atrial fibrillation drivers

Novel device can benefit patients with upper limb paralysis

Brain-computer interface enables patients with severe paralysis to resume daily tasks

Physical stress caused by interruptions in workplace

Deep learning models help hunt for COVID-19 drugs

Novel machine learning algorithm helps find drug binding sites

Researchers investigate how brain signaling gives rise to decision-making

New tool predicts prognosis of individual patients with COVID-19

Researchers identify molecular processes in kidney cells that attract and feed COVID-19

Molecular processes in kidney cells may increase diabetics' vulnerability to COVID-19 infection

Researchers propose using complexity science to respond better to the COVID-19 pandemic

Novel tool can provide rapid stroke diagnosis from interaction with a smartphone

Researchers successfully perform terahertz imaging of early-stage breast cancer without staining

Brain imaging biomarker may help predict treatment response in patients with psychiatric disorders, study reveals

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