Schizophrenia Study Suggests Advanced Genetic Scorecard Cannot Predict a Patient’s Fate

Researchers at the Icahn School of Medicine at Mount Sinai found that a tool commonly used in research for evaluating a person’s genetic risk for a disease, called a polygenic risk score, was no better at predicting the outcome of a schizophrenia patient’s disease over time than written reports. The results raise important questions about the use of polygenic risk scores in real-world, clinical situations, and also suggest that a doctor’s written report may be an untapped source of predictive information.

UC San Diego Health Adopts SMART Health Card for Digital Vaccine Records

UC San Diego Health is now offering a verifiable digital vaccine record to its patients who have or will receive a COVID-19 vaccine. These secure online records, otherwise known as a SMART health card, can be accessed directly from the MyUCSDChart patient portal.

The Mount Sinai Hospital Recognized as No. 4 on Newsweek’s World’s Best Smart Hospital 2021 List

The Mount Sinai Hospital is ranked No. 1 in the New York City metropolitan area and No. 4 globally among the most technologically advanced health care institutions on Newsweek’s list of “The World’s Best Smart Hospitals 2021.”

Research News Tip Sheet: Story Ideas from Johns Hopkins Medicine

During the COVID-19 pandemic, Johns Hopkins Medicine Media Relations is focused on disseminating current, accurate and useful information to the public via the media. As part of that effort, we are distributing our “COVID-19 Tip Sheet: Story Ideas from Johns Hopkins” every other Wednesday.

Research News Tip Sheet: Story Ideas from Johns Hopkins Medicine

During the COVID-19 pandemic, Johns Hopkins Medicine Media Relations is focused on disseminating current, accurate and useful information to the public via the media. As part of that effort, we are distributing our “COVID-19 Tip Sheet: Story Ideas from Johns Hopkins” every other Wednesday.

Mount Sinai Researchers Build Models Using Machine Learning Technique to Enhance Predictions of COVID-19 Outcomes

Mount Sinai researchers have published one of the first studies using a machine learning technique called “federated learning” to examine electronic health records to better predict how COVID-19 patients will progress.

Mount Sinai Researchers Build Models Using Machine Learning Technique to Enhance Predictions of COVID-19 Outcomes

Mount Sinai researchers have published one of the first studies using federated learning to examine electronic health records to better predict how COVID-19 patients will progress.

Mount Sinai Develops Machine Learning Models to Predict Critical Illness and Mortality in COVID-19 Patients

Mount Sinai researchers have developed machine learning models that predict the likelihood of critical events and mortality in COVID-19 patients within clinically relevant time windows.

Making telemedicine more accessible to vulnerable, underserved populations

UCLA’s Dr. Alejandra Casillas has had a longtime interest in health disparities, with a particular focus on health communications among underserved and limited English proficient communities. This is what she’s doing about it.

Opioid Use Disorder? Electronic Health Records Help Pinpoint Probable Patients

A new study suggests that patients with opioid use disorder may be identified using information available in electronic health records, even when diagnostic codes do not reflect this diagnosis. The study demonstrates the utility of proxies coding for DSM-5 criteria from medical records to generate a quantitative DSM-5 score that is associated with opioid use disorder severity. The study methods are unique in deriving a severity score that aims to mirror severity scores from more traditional interview-based diagnostic procedures.

COVID-19 may have been in L.A. as early as last December, UCLA-led study suggests

UCLA researchers and colleagues who analyzed electronic health records found that there was a significant increase in patients with coughs and acute respiratory failure at UCLA Health hospitals and clinics beginning in late December 2019, suggesting that COVID-19 may have been circulating in the area months before the first definitive cases in the U.S. were identified. This sudden spike in patients with these symptoms, which continued through February 2020, represents an unexpected 50% increase in such cases when compared with the same time period in each of the previous five years.

Researchers @UCSDMedSchool found that using electronic-based consent forms (eConsents) decreased error rates from 32% to 1%, helping to decrease delays to surgery.

In a recent study published in JAMA Surgery, researchers at University of California San Diego School of Medicine found that using electronic-based consent forms (eConsents) decreased the error rate from 32 percent to 1 percent. “You are not relying on…

Weizmann Scientists Devise New Algorithm that Predicts Gestational Diabetes

Using machine learning to analyze data on nearly 600,000 pregnancies, researchers devised an algorithm that identified nine parameters – out of more than 2,000 analyzed – that can predict which women are at risk of gestational diabetes. The parameters can identify risk early in – even before – pregnancy, enabling early intervention.