AI Medical Compendium

Glucose forecasting and hypoglycemia forewarning in type 1 and type 2 diabetes using deep learning.

iScience Mar 10, 2026

Hypoglycemia is a major barrier to safe diabetes management. Although deep learning has been widely applied to blood glucose (BG) prediction, most studies provide limited hypoglycemia forewarning and are trained on small type 1 diabetes cohorts with ... read more

Smart Microfluidics: A curated dataset of microfluidic liposome formulations with cross-laboratory validation for machine-learning applications.

Data in brief Mar 9, 2026

This dataset documents microfluidic production runs of liposome formulations generated across two independent laboratories using standardized lipid compositions and controlled flow conditions. The data include formulation parameters, microfluidic ope... read more

Quality assessment and geographical origin traceability of Gastrodia elata based on machine vision, flash GC e-nose, HPLC, and machine learning algorithms.

Food research international (Ottawa, Ont.) Mar 9, 2026

Gastrodia elata Bl. (GE), a widely utilized edible and functional material, exhibits notable quality variations due to distinct growing conditions across different geographical origins, making reliable methods for origin authentication and quality ev... read more

Artificial Intelligence: The Cutting-Edge Research Companion.

Clinical spine surgery Mar 9, 2026

Artificial intelligence (AI) represents a paradigm-shifting technology that empowers computers and software to emulate human intelligence by processing vast amounts of data. Its ubiquitous utilization continues to expand across diverse domains. AI so... read more

Identifying and timing patient outcomes in clinician notes using large language models.

Artificial intelligence in medicine Mar 9, 2026

BACKGROUND: Key challenges in leveraging unstructured clinician notes for predictive models include identifying and timing patient outcomes. To address these challenges we applied large language models (LLMs) to identify and temporally localize patie... read more

DisNet : Learning interpretable depression representations in speech.

Neural networks : the official journal of the International Neural Network Society Mar 9, 2026

Speech-based depression detection (SDD) offers an objective and convenient method for depression screening and intervention. However, existing deep learning methods lack interpretability, which prevents them from revealing their findings for the quan... read more

Fusing serum peptidome profiles with clinical variables via machine learning for pulmonary embolism risk assessment.

Talanta Mar 9, 2026

Pulmonary embolism (PE) remains a life-threatening cardiovascular emergency that requires timely and accurate diagnosis. Current diagnostic strategies rely heavily on computed tomography pulmonary angiography (CTPA), which, although highly specific, ... read more

Uncovering Clinically Relevant Breast Cancer Subtypes Biomarkers Using Integrative Bioinformatics and Machine Learning Approaches.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals Mar 9, 2026

A precise diagnosis and customized treatment become more difficult by the genomic heterogeneity of breast cancer (BRCA). In order to examine gene expression data from two separate Gene Expression Omnibus (GEO) microarray datasets, we used a integrati... read more

The Brain-Age Gap in Pediatric Dystonia: Neuroanatomical Deviations Inform Deep Brain Stimulation Outcomes.

Movement disorders : official journal of the Movement Disorder Society Mar 9, 2026

BACKGROUND: Dystonia in children is a heterogeneous condition with variable response to deep brain stimulation (DBS). Brain-age gap, a machine learning-derived metric of structural deviation from norm, may capture signatures that differentiate underl... read more

Bridging Atomistic Simulations and Reservoir Computing for Predicting Structural and Transport Properties of Thiol-Ene Click-Cross-Linked Carboxymethyl Cellulose Hydrogels.

The journal of physical chemistry. B Mar 9, 2026

The long-time scale behavior of hydrogels is still a core problem in material design, especially due to the limitation of computational cost and accessibility time scale of molecular dynamics (MD) simulations. So, this study offered a combined model,... read more

Artificial Intelligence Medical Compendium