Researchers have identified azole compounds, especially talarozole, as promising drug candidates for Leigh syndrome by combining deep learning computational screening with human brain organoid models derived from patient cells. Original paper: Accelerating Leigh syndrome drug discovery through deep learning screening in brain organoids. — Nature Communications. 10.1038/s41467-026-71391-2 📄 Read the article

A novel two-stage deep learning model significantly improves histological diagnosis of early pregnancy loss, achieving 84.3% accuracy while reducing diagnostic time and substantially aiding pathologist decision-making. Original paper: Patch-to-slide fusion deep learning model for histological diagnosis of early pregnancy loss including hydatidiform mole. — NPJ digital medicine. 10.1038/s41746-026-02628-z 📄 Read the article

A specialized large language model called Xuanwu-NeuroAid outperformed emergency physicians in diagnosing neurological emergencies and significantly improved physician accuracy when used as a decision-support tool. Original paper: Development and prospective shadow evaluation of a domain-specific large language model for emergency neurological diagnosis. — NPJ digital medicine. 10.1038/s41746-026-02644-z 📄 Read the article

Artificial intelligence models developed from gene expression data can accurately predict papillary thyroid carcinoma occurrence and cervical lymph node metastasis risk, potentially enabling more personalized patient care. Original paper: Predictive models for the occurrence and lymph node metastasis of papillary thyroid carcinoma with regional risk heterogeneity. — NPJ digital medicine. 10.1038/s41746-26-00123 📄 Read the article

Researchers have developed RBT-GC, a blood-based biomarker that identifies high-risk gastric cancer patients among those with chronic dyspepsia, dramatically outperforming traditional tumor markers like CEA and CA19.9. Original paper: Development and validation of a novel blood-based biomarker for gastric cancer triage in chronic dyspepsia. — NPJ digital medicine. 10.1038/s41746-026-02618-1 📄 Read the article

Your mouth’s bacterial community may hold the key to predicting biological age and disease risk. Researchers have shown that oral microbiome signatures independently forecast mortality and frailty, offering a practical clinical biomarker. Original paper: Oral microbiome signatures predict biological age and host health. — Nature communications. 10.1038/s41467-026-72096-2 📄 Read the article

A multi-center study demonstrates that combining PET/CT and MRI with machine learning significantly improves detection of clinically significant prostate cancers. Original paper: Non-invasive diagnosis strategy integrating PSMA PET/CT and mpMRI for patients with suspected prostate cancer: a multi-center study. — BMC medicine. 10.1186/s12916-026-04859-z 📄 Read the article

Researchers have developed an interpretable AI system that combines baseline PET/CT imaging with electronic health records to predict progression-free survival and overall survival in mantle cell lymphoma patients with unprecedented accuracy. Original paper: Interpretable multimodal PET/CT-EHR fusion via mixture-of-experts for prognostic stratification in mantle cell lymphoma: a multicenter study. — BMC medicine. 10.1186/s12916-026-04865-1 📄 Read the article

A new automated deep learning system can detect focal liver lesions in ultrasound videos in real-time, and critically, it levels the playing field—helping less experienced sonographers match the performance of veteran specialists. Original paper: Automated deep learning for real-time focal liver lesions detection in ultrasound videos a multicenter study. — NPJ digital medicine. 10.1038/s41746-026-02629-y 📄 Read the article

A novel deep learning model combining digital pathology with clinical data accurately predicts early recurrence in gastric cancer, while identifying a subset of patients with immune-activated tumors potentially responsive to immunotherapy. Original paper: A deep learning-based digital biopsy for predicting early recurrence in gastric cancer. — Nature communications. 10.1038/s41467-026-71347-6 📄 Read the article