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TL;DR: A 2026 Scientific Reports study reported that machine learning models classified brain tumor MRI images across four categories with high internal accuracy, led by a convolutional neural network at 99.29% on a single public dataset. Key Findings 7,023 MR…
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TL;DR: A 2026 machine-learning study in PLOS One used student mental-health survey features to test an interpretable FT-Transformer plus LSTM model, which reached 95% accuracy for low, medium, and high risk prediction in a public dataset. Key Findings 95% accu…
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TL;DR: A 2026 study in Journal of Affective Disorders used interpretable machine learning to predict who completed more prompts during a 14-day mindfulness app trial for generalized anxiety disorder. Key Findings Trial size: A two-arm randomized trial included…
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TL;DR: A 2026 preprint in medRxiv reported that an interpretable CatBoost machine-learning model predicted stroke-associated pneumonia after acute ischemic stroke bridging therapy with a test-set AUC of 0.932, with 7-day stroke severity and early inflammatory…
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TL;DR: A 2026 analysis in Journal of Korean Medical Science identified PIK3CG, PRKCD, and TRIM22 as glioblastoma gene markers linked to worse survival and stronger immune-activity signals in IDH-wildtype tumors. Key Findings 12,041-gene screen: Researchers scr…
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TL;DR: A 2026 study in npj Mental Health Research found that a 308-person multimodal MRI study found treatment-resistant depression carried a distinct structure-function decoupling pattern, and machine-learning models separated TRD from non-resistant depressio…
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TL;DR: A 2026 preprint in medRxiv trained machine-learning models on Danish electronic health records and found that an XGBoost model predicted clozapine initiation within 365 days with an AUROC of 0.81 in patients with schizophrenia or schizoaffective disorde…
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TL;DR: A 2026 study in Nature Mental Health describes an AI system that scans routine electronic health records (EHRs) and combines early-life visits, prescriptions, and comorbidities into a risk flag for ADHD evaluation before formal diagnosis. Key Findings A…
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TL;DR: A 2026 article-in-press study in Alzheimer’s Research & Therapy found that olfactory-region MRI radiomics, a method that turns brain scans into quantitative texture and shape features, linked blood pTau217, a tau-related Alzheimer’s disease biomarker, w…
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TL;DR: A 2026 machine-learning study found that the final SNP-NF model in PLOS One reported mAUC 0.965, recall 0.929, and precision 0.929, while the study reported gains of about 3% in mAUC, 1% in precision, and 0.7% in recall versus their previous neural-proc…
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