AI Medical Compendium

An Integrated AIVIVE-PBPK-QIVIVE Framework with HTTK Validation for Probabilistic Risk Assessment of Neodymium Nitrate.

Chemical research in toxicology May 4, 2026

Rare earth elements (REEs) are critical to modern industries but pose growing health risks due to increasing environmental release, and neodymium nitrate (Nd(NO3)3), a representative REE compound, lacks comprehensive toxicological data. To address th... read more

Adaptive Deep Learning for High-Fidelity Quantitative Single-Molecule Imaging.

Analytical chemistry May 4, 2026

Accurate quantification of molecular dynamics in live cells is critical for elucidating receptor signaling and guiding therapeutic strategies. Yet current deep learning methods for fluorescence imaging often distort intensity and lack robustness unde... read more

Energy- and Area-Efficient Ionic-Switch Activation Neuron for Monolithic 3D Neural Network Architectures.

ACS nano May 4, 2026

To overcome the bottleneck inherent in the von Neumann architecture and advance hardware-oriented neural network design, this study conceptually proposes a monolithic three-dimensional, vertically integrated neural network architecture that supports ... read more

CypGEM: A Geometry-Aware and Edge-Enhanced Graph Transformer Model for Predicting Sites of Metabolism Mediated by Cytochromes P450.

Journal of chemical information and modeling May 4, 2026

Accurate prediction of a compound's site(s) of metabolism (SoMs) mediated by cytochromes P450 (CYP450) is advantageous in the early stage of drug discovery. However, existing computational methods often struggle to explicitly capture the microscopic ... read more

Machine learning assisted prediction of the compressive response of porous metallic bio-metamaterials.

Computer methods in biomechanics and biomedical engineering May 4, 2026

This study leverages deep feed-forward neural networks (DNNs) to develop a predictive model for estimating the compressive behavior of porous metallic bio-metamaterials based on their geometric and material characteristics. A DNN architecture compris... read more

Protocol for cerebrospinal fluid analysis using enrichment-enhanced surface-enhanced Raman spectroscopy and transformer-enabled spectral classification.

STAR protocols May 4, 2026

The rapid detection and precise classification of cerebrospinal fluid in acute leukemia patients constitute a crucial clinical imperative. Here, we present a protocol for cerebrospinal fluid analysis deep learning with enrichment-enhanced surface-enh... read more

CADS: A Causal Inference Framework for Identifying Essential Genes to Enhance Drug Synergy Prediction.

Bioinformatics (Oxford, England) May 4, 2026

MOTIVATION: Drug synergy is crucial for developing effective combination therapies, but traditional screening methods suffer from inefficiency and high costs. While deep learning shows promise for predicting drug synergy, current approaches using Tra... read more

Neutrophil extracellular traps-related biomarkers in idiopathic pulmonary arterial hypertension: A machine learning-based identification and experimental validation study.

Molecular immunology May 4, 2026

Neutrophil extracellular traps (NETs) are increasingly recognized as critical mediators in vascular inflammation and remodeling, yet their molecular mechanisms in idiopathic pulmonary arterial hypertension (IPAH) pathogenesis remain largely unexplore... read more

High-precision stress prediction using deep energy network enhanced by stress equilibrium with Delaunay integration on refined grid.

Cell reports methods May 4, 2026

We present the deep energy method enhanced by stress equilibrium (DEM-SE), a physics-informed neural network (PINN) architecture for high-precision prediction of complex stress fields in elastic plates. The method calculates total potential energy vi... read more

Development and validation of a risk stratification model for sarcopenia in patients with chronic lung disease: a cross-sectional study based on CHARLS data.

BMJ open respiratory research May 4, 2026

OBJECTIVE: The aim of this study was to develop a machine learning-based stratification model to identify high-risk individuals for sarcopenia among patients with chronic lung disease (CLD), thereby facilitating early personalised management of this ... read more

Artificial Intelligence Medical Compendium