Research

A Machine-Learning Approach to Finding Treatment Options for COVID-19

When the COVID-19 pandemic struck in early 2020, doctors and researchers rushed to find effective treatments. There was little time to spare. "Making new drugs takes forever," says Caroline Uhler, a computational biologist in MIT's Department of Electrical Engineering and Computer Science and the Institute for Data, Systems and Society, and an associate member of the Broad Institute of MIT and Harvard.

Computational Medicine - Moving from Uncertainty to Precision

Individual choices in medicine carry a certain amount of uncertainty.

An innovative partnership at The University of Texas at Austin takes aim at medicine down to the individual level by applying state-of-the-art computation to medical care.

Wearable Devices can Detect COVID-19 Symptoms and Predict Diagnosis

Wearable devices can identify COVID-19 cases earlier than traditional diagnostic methods and can help track and improve management of the disease, Mount Sinai researchers report in one of the first studies on the topic. The findings were published in the Journal of Medical Internet Research on January 29.

Researchers Develop Data Tool that may Improve Care

With the aid of sophisticated machine learning, researchers at UPMC and the University of Pittsburgh School of Medicine demonstrated that a tool they developed can rapidly predict mortality for patients facing transfer between hospitals in order to access higher-acuity care. This research, published today in PLOS One, could help physicians, patients and their families avoid unnecessary hospital transfers and low-value treatments, while better focusing on the goals of care expressed by patients.

New Neural Network Enables Easy Screening of Sleep Apnoea in Patients with Cerebrovascular Disease

A new neural network developed by researchers at the University of Eastern Finland and Kuopio University Hospital enables an easy and accurate assessment of sleep apnoea severity in patients with cerebrovascular disease. The assessment is automated and based on a simple nocturnal pulse oximetry, making it possible to easily screen for sleep apnoea in stroke units.

COVID-19 Warnings Were on Twitter Well Before the Outbreak of the Pandemic

Even before public announcements of the first cases of COVID-19 in Europe were made, at the end of January 2020, signals that something strange was happening were already circulating on social media. A new study of researchers at IMT School for Advanced Studies Lucca, published in Scientific Reports, has identified tracks of increasing concern about pneumonia cases on posts published on Twitter in seven countries, between the end of 2019 and the beginning of 2020.

Using Artificial Intelligence to Find New Uses for Existing Medications

Scientists have developed a machine-learning method that crunches massive amounts of data to help determine which existing medications could improve outcomes in diseases for which they are not prescribed.

The intent of this work is to speed up drug repurposing, which is not a new concept - think Botox injections, first approved to treat crossed eyes and now a migraine treatment and top cosmetic strategy to reduce the appearance of wrinkles.

Research News

A Machine-Learning Approach to Finding Treatment Options for COVID-19

Computational Medicine - Moving from Uncertainty to Precision

Wearable Devices can Detect COVID-19 Symptoms and Predict Diagnosis

Researchers Develop Data Tool that may Improve Care

New Neural Network Enables Easy Screening of Sleep Apnoea in Patients with Cerebrovascular Disease

COVID-19 Warnings Were on Twitter Well Before the Outbreak of the Pandemic

Using Artificial Intelligence to Find New Uses for Existing Medications

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