A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

More than a decade ago, researchers launched the BabySeq Project, a pilot program to return newborn genomic sequencing results to parents and measure the effects on newborn care. Today, over 30 ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

A novel machine learning framework – Mal-ID – can decipher an individual’s immune system’s record of past infections and diseases, according to a new study, providing a powerful tool with the ...

Machine learning accurately predicts peak and average IOP, aiding glaucoma management by informing treatment decisions. Random forest regression (RFR) outperformed ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Scientist Yi Nian is sharing his machine-learning expertise with the world in his latest co-authored publication, “Globally Interpretable Graph Learning via Distribution Matching.” SEATTLE, Wash. - ...

Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the ...

A machine learning model can predict hepatocellular carcinoma (HCC) risk using routinely available data, according to a study published online March 30 in Cancer Discovery. Jan Clusmann, M.D., from ...