Risk Assessment

Risk Stratification May Reduce Unnecessary Pediatric Oophorectomies

October 5, 2023 - A consensus-based, preoperative risk stratification algorithm may help reduce unnecessary oophorectomies in pediatric and adolescent patients with benign ovarian disease, according to a study published this week in JAMA. The authors indicated that most ovarian masses in pediatric patients are benign, but these are commonly managed via oophorectomy,...

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Pancreatic Cancer Prediction Model May Reduce Unnecessary Biopsies

by Shania Kennedy

Researchers have developed and externally validated a prediction model to detect early-stage pancreatic cancer using routinely collected blood biomarkers, according to a recent study published in JAMA...

Clinicians May Be Unprepared for Widespread CDS Algorithm Integration

by Shania Kennedy

In a perspective article recently published in the New England Journal of Medicine, researchers from the University of Maryland School of Medicine (UMSOM) and Beth Israel Deaconess Medical Center...

Deep Learning Model Detects Diabetes Using Routine Chest Radiographs

by Shania Kennedy

Researchers at Emory University have validated a deep learning (DL) model capable of detecting early warning signs of diabetes using routinely collected chest radiographs and electronic health record...

Research Identifies Link Between Genetic Makeup and Disease Risk

by Mark Melchionna

Using data from the UCLA ATLAS Precision Health Biobank, UCLA Health researchers found differences in diagnoses, hospital use, and genetic disease across various populations, which provided them with a...

VA Study to Develop AI for Aggressive Prostate Cancer Prediction

by Shania Kennedy

The United States Department of Veterans Affairs (VA) has launched a new study in which researchers from five VA medical centers will work to develop an artificial intelligence tool that can predict...

ADA Sessions Showcase Diabetic Retinopathy AI, Artificial Pancreas

by Shania Kennedy

During the 83rd Scientific Sessions held by the American Diabetes Association (ADA) in San Diego, California, over the weekend, researchers presented studies detailing advancements in diabetes care...

AI Algorithms Outperform Standard Models in Cancer Prediction

by Mark Melchionna

Research from the Radiological Society of North America (RSNA) indicates that artificial intelligence (AI) algorithms performed better than the Breast Cancer Surveillance Consortium (BCSC) risk model...

Machine Learning Tools Flag Predictors of Fetal Heart Rate Changes

by Shania Kennedy

Researchers have developed machine learning (ML) methods that can accurately identify predictors associated with fetal heart rate changes following neuraxial analgesia in healthy pregnant patients,...

Potential Racial Bias Found in Type 2 Diabetes Risk Prediction Models

by Shania Kennedy

Artificial intelligence (AI) algorithms used to screen for and predict type 2 diabetes may be racially biased, which could perpetuate health disparities, according to a study published last week in...

ML Highlights Population Differences in Long COVID Risk, Symptoms

by Shania Kennedy

Researchers from Weill Cornell Medicine using machine learning (ML)-based analysis of electronic health record (EHR) data found that long COVID risk and symptoms present differently across diverse...

Machine-Learning Model Provides Predictions on Physician Turnover

by Mark Melchionna

A recent study by Yale University researchers detailed the creation of a machine-learning model that can assist researchers in determining physician turnover, enabling healthcare organizations to...

New Risk Score Tool Provides Accurate Predictions of Dementia Patterns

by Mark Melchionna

Published in JAMA Network Open, a recent study described the development and accuracy of a risk score tool that predicts individual dementia risk, providing clinical teams with guidance on timely...

AI Can Help Improve Identification of High-Cost Health Plan Members

by Mark Melchionna

A recent study published in the American Journal of Managed Care found that identifying high-cost members was made easier through the implementation of artificial intelligence (AI) and the analysis of...

New Screening Tool Effective in Detecting Pediatric Asthma Risk

by Mark Melchionna

A study published in JAMA Network Open concluded that a newly developed symptom-based screening tool could detect asthma risk levels among pediatric patients as well as persistent wheezing symptoms and...

Penn State to Use Artificial Intelligence to Perform Health Risk Predictions

by Mark Melchionna

Following the receipt of a $599,883 grant from the National Science Foundation (NSF), Penn State researchers plan to create artificial intelligence (AI)-based machine learning (ML) algorithms that can...

Researchers to Create AI Algorithms That Predict Patient Risk for Rare Diseases

by Mark Melchionna

Researchers from the Perelman School of Medicine at the University of Pennsylvania and the University of Florida College of Medicine are creating a set of artificial intelligence (AI) algorithms to...

New Mayo Clinic Artificial Intelligence Model Provides Labor Risk Predictions

by Mark Melchionna

To meet the varied healthcare needs of pregnant women, Mayo Clinic researchers created an artificial intelligence (AI)-based risk prediction model that uses labor characteristics to indicate potential...

Machine-Learning Models May Accurately Predict Postpartum Hemorrhage Risk

by Shania Kennedy

A new study published in the Journal of Medical Internet Research shows that machine-learning (ML) models can effectively predict the risk of postpartum hemorrhage using data pulled from de-identified...

AI Tool Can Identify Sepsis Within 12 Hours of Hospital Admission

by Shania Kennedy

A new study published in JAMA Network Open assesses an artificial intelligence (AI) tool that can predict the likelihood of patients developing sepsis and the severity of the infection as quickly as 12...

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