Current medical AI articles

Unveiling System Dynamics with Neural Symbolic Regression One-Sentence Summary The paper introduces a computational tool, Learning Law of Changes (LLC), that combines neural networks and symbolic regression to automatically discover the mathematical equations governing complex network dynamics from observational data. Overview Understanding the behavior of complex systems, such as biological networks or epidemic spreads, is…

Title AI Smart Glasses in Digital Health One-Sentence Summary This systematic literature review analyzes 101 studies to assess the current applications, benefits, and challenges of integrating AI-powered smart glasses into digital health for proactive and personalized healthcare. Overview This paper systematically reviews the integration of AI-powered smart glasses into digital health management. The authors analyzed…

Title Stem-like cells in pediatric T-ALL relapse One-Sentence Summary This study uses single-cell RNA sequencing to identify a subpopulation of quiescent, stem-like leukemia cells in pediatric T-cell acute lymphoblastic leukemia that resists chemotherapy and expands at relapse. Overview Relapse in pediatric T-cell acute lymphoblastic leukemia (T-ALL) is associated with a poor prognosis, often driven by…

Title T-ALL relapse linked to stem-like cancer cells One-Sentence Summary This study identifies a subpopulation of quiescent, stem-like leukemia cells that resists chemotherapy and expands at relapse in pediatric T-cell acute lymphoblastic leukemia, linking their presence at diagnosis to higher treatment failure risk. Overview While treatment for pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved,…

Title Stem-like Cells Drive T-ALL Relapse One-Sentence Summary This study identifies a subpopulation of quiescent, stem-like leukemia cells that expands at relapse in pediatric T-cell acute lymphoblastic leukemia, linking their chemotherapy resistance to specific transcriptional and splicing programs. Overview Relapse in pediatric T-cell acute lymphoblastic leukemia (T-ALL) is associated with chemotherapy resistance and poor outcomes.…

Title AI Spatial Analysis of Immune Cells in Pancreatic Cancer One-Sentence Summary This study demonstrates that an artificial intelligence-powered analysis of immune cell distribution in resected pancreatic cancer tissue can classify tumors into distinct immune phenotypes that strongly predict patient survival outcomes. Overview Predicting outcomes for pancreatic ductal adenocarcinoma (PDAC) is a significant challenge. While…