A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

Circular RNAs (circRNAs), recognized as covalently closed, single-stranded RNA molecules formed through reverse splicing, are characterized by their unique ring structures, site-specific splicing, and ...

A newly revealed molecular tug-of-war may have implications for better understanding how a multitude of diseases and ...

The clinical and biological features proposed here in conjunction with ML can improve the interpretation of CRC mechanisms and predict patient ...

AI therapeutics company built on causal biology, today announced the publication of research in Nature Communications validating its POSH (Pooled Optical Screening in Human cells) platform. The study ...

Analyzing stochastic cell-to-cell variability can potentially reveal causal interactions in gene regulatory networks.

Researchers have developed a novel approach to detect ALS and predict survival by measuring genetic activity in blood cells, a study found.

Researchers developed a blood test that spots ALS with 90% accuracy. The 46-gene panel could cut diagnostic delays that now ...

Today at the San Antonio Breast Cancer Symposium (SABCS), researchers presented the initial findings from a major multi-year collaboration between the ECOG-ACRIN Cancer Research Group (ECOG-ACRIN) and ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests. They ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Using machine learning models, researchers have identified a potential way to diagnose amyotrophic lateral sclerosis earlier ...