AI Medical Compendium

Whole-brain connectome analysis for elucidating specific structural neural networks in idiopathic normal-pressure hydrocephalus.

Magma (New York, N.Y.) Apr 21, 2026

OBJECTIVE: To test the hypothesis that idiopathic normal-pressure hydrocephalus (iNPH) is also associated with reproducible whole-brain structural connectivity reductions detectable by diffusion MRI connectomics, beyond the established clinical triad... read more

Automated Deep Learning-Based Demyelination Load Segmentation in Metachromatic Leukodystrophy.

Clinical neuroradiology Apr 21, 2026

PURPOSE: Metachromatic leukodystrophy (MLD) is a rare lysosomal storage disorder characterized by progressive white matter demyelination. Quantification of demyelinated white matter on MRI-typically expressed as the demyelination load-serves as a key... read more

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

Diabetologia Apr 21, 2026

AIMS/HYPOTHESIS: Clinically actionable biomarkers that accurately reflect the health status of the beta cell are needed to improve risk stratification and optimise the timing of interventions in type 1 diabetes. We hypothesised that inflammatory stre... read more

TripleBind: a generalizable deep learning framework for protein-nucleic acid and protein-ligand binding sites prediction based on pre-trained protein language models.

Molecular diversity Apr 21, 2026

Harnessing machine learning and multi-scale modeling to discover novel ALOX15 inhibitors from marine natural products.

Molecular diversity Apr 21, 2026

ALOX15 is a key regulatory enzyme in multiple pathological processes including inflammation, cancer, and cardiovascular disease, rendering the development of potent inhibitors of this enzyme of significant clinical importance. This study aims to scre... read more

Deep learning-based early prediction of carotid plaque response to lipid-lowering therapy using longitudinal multimodal ultrasound imaging.

Insights into imaging Apr 21, 2026

OBJECTIVE: This study aimed to develop and validate a deep learning prediction model using longitudinal multimodal ultrasound imaging for early identification of treatment-sensitive and treatment-resistant carotid plaques in patients receiving lipid-... read more

Patient-Initiated Permanent Deletion of Their Electronic Health Record Data: implications for Artificial Intelligence and Big Data in Healthcare : Clyde T. Matava, MBChB, MMed, MHSc.

Journal of medical systems Apr 21, 2026

Artificial intelligence-based screening of phytochemicals for targeted cancer therapy.

Natural products and bioprospecting Apr 21, 2026

Cancer remains one of the leading causes of death worldwide and continues to pose a serious public health challenge. The limited success of many current treatments-often due to toxicity, poor selectivity, and the development of drug resistance-highli... read more

Identification of Autophagy-related Genes of the Osteoarthritis Using Machine Learning Algorithm.

Biochemical genetics Apr 21, 2026

ICMJE Recommendations (2026) on the Use of Artificial Intelligence in Scientific Writing.

Indian pediatrics Apr 21, 2026

Artificial Intelligence Medical Compendium

Whole-brain connectome analysis for elucidating specific structural neural networks in idiopathic normal-pressure hydrocephalus.

Automated Deep Learning-Based Demyelination Load Segmentation in Metachromatic Leukodystrophy.

Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.

TripleBind: a generalizable deep learning framework for protein-nucleic acid and protein-ligand binding sites prediction based on pre-trained protein language models.

Harnessing machine learning and multi-scale modeling to discover novel ALOX15 inhibitors from marine natural products.

Deep learning-based early prediction of carotid plaque response to lipid-lowering therapy using longitudinal multimodal ultrasound imaging.

Patient-Initiated Permanent Deletion of Their Electronic Health Record Data: implications for Artificial Intelligence and Big Data in Healthcare : Clyde T. Matava, MBChB, MMed, MHSc.

Artificial intelligence-based screening of phytochemicals for targeted cancer therapy.

Identification of Autophagy-related Genes of the Osteoarthritis Using Machine Learning Algorithm.

ICMJE Recommendations (2026) on the Use of Artificial Intelligence in Scientific Writing.

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