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2 articles from the last 90 days matching "machine learning"

Clinical trialUNITERAREMay 4

New Recruiting Trial: Machine Learning Prediction of Disease Progression in Adolescent Idiopathic Scoliosis

Researchers at Istanbul University are looking for adolescents with idiopathic scoliosis (abnormal spine curvature) to participate in a study starting in April 2026. The study will use artificial intelligence and machine learning to predict which patients' scoliosis will get worse over time. This could help doctors identify who needs treatment sooner and who can be monitored safely without surgery.

WHY IT MATTERSIf successful, this machine learning tool could help doctors predict which adolescents with scoliosis will need surgery before their curves become severe, potentially avoiding unnecessary procedures for those whose curves stabilize naturally.
👁 Watch this spaceAdolescent Idiopathic Scoliosis
ResearchBIORXIVApr 17

Preprint: The results of Transcriptome-wide Mendelian Randomization (TWMR) in large-scale populations can directly validate, across scales, the results of causal inference from deep learning combined with double machine learning on single-cell transcriptomes of human samples.

Scientists are testing a new way to understand how genes cause diseases by combining two different research methods: one that studies genes in large groups of people, and another that looks at individual cells in the lab. This study checks whether both methods give the same answers, which would help researchers trust their findings more and move treatments from the lab to real patients faster.

WHY IT MATTERSIf validated, this approach could accelerate how researchers identify disease-causing genes in rheumatologic conditions, potentially leading to faster development of targeted treatments for patients with autoimmune and inflammatory diseases.
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