AI Finds Promising Drugs for Liver Cancer and Lung Fibrosis
Michigan State researchers use machine learning to predict gene effects from chemical structures, identifying compounds that reduced tumors in mice.
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Michigan State researchers use machine learning to predict gene effects from chemical structures, identifying compounds that reduced tumors in mice.
EMBL scientists use AI to spot the earliest markers of chromosomal chaos in cells, finding one in ten divisions produces errors that can seed tumors.
Betsi Cadwaladr health board uses Paige AI to triage biopsies, catching malignancies that would otherwise sit in queues for three months
University of Geneva researchers create MangroveGS, an AI that reads gene expression patterns to forecast which cancers will metastasize.
University of Geneva's MangroveGS uses gene signatures to forecast metastasis risk, potentially sparing low-risk patients from aggressive treatment
GEMINI study finds AI integration catches cancers missed by radiologists while cutting workload by a third
Machine learning models screened 1.6 million potential drug pairings and identified synergistic combinations that neither drug achieves alone. Lab tests confirmed the predictions work.
Google DeepMind and Yale's 27B parameter model identified how silmitasertib plus interferon can boost cancer antigen presentation by 50%
CleaveNet system designs peptide sensors that detect cancer-linked enzymes, potentially enabling at-home screening for dozens of cancer types
An Emory study found that pairing clinical staff with AI tools improved accuracy in identifying eligible cancer patients without adding to workload.
Valar Labs publishes JCO study showing its AI can identify optimal chemotherapy from routine pathology slides, with patients living nearly 3 months longer when matched to predicted treatment.