AI Medical Compendium

Personalizing In-Vehicle warnings: A causal machine learning approach to optimizing workload and risk perception.

Accident; analysis and prevention Apr 15, 2026

The effectiveness of in-vehicle Connected Information (CI) is often limited by uniform warning strategies that overlook the interaction among warning design, traffic context, and driver state. This study establishes a causal machine learning framewor... read more

Cone-Beam Computed Tomography-Based Three-Dimensional Phenotypes of Skeletal Class II Malocclusion in Yemeni Adults: A Principal Component and Cluster Analysis.

International dental journal Apr 15, 2026

INTRODUCTION AND AIMS: Skeletal Class II malocclusion is heterogeneous, and conventional two-dimensional cephalometry may not fully capture relevant three-dimensional (3D) craniofacial variation. This study aimed to identify 3D skeletal phenotypes of... read more

Evaluating Large-Language Models Against Providers on Surgical Diagnostic Reasoning Tasks.

The Journal of surgical research Apr 15, 2026

INTRODUCTION: Large language models (LLMs) have shown efficacy in surgery-related tasks such as literature screening and performing well on-board examination; however, their utility in diagnostic reasoning remains unclear. We assessed the accuracy an... read more

Speaking Patient's Language: Assessment of Readability and Fidelity of Artificial Intelligence-Optimized Consent Forms.

The Journal of surgical research Apr 15, 2026

INTRODUCTION: Informed consent requires patients to fully comprehend the risks, benefits, and alternatives of an intervention. The American Medical Association and the National Institutes of Health recommend patient-facing materials be written at a s... read more

Machine learning-driven source apportionment and health risk assessment of multi-source groundwater pollution in highly permeable aquifers: A case study in Southwest China.

Journal of environmental management Apr 15, 2026

Industrial expansion releases multiple pollutants into groundwater, whose migration in highly permeable aquifers is governed by rapid flow through coarse sediments or fractured bedrock. This dynamic flow disperses and blends contaminant plumes from d... read more

A tri-modal contrastive learning framework for protein representation learning.

Cell reports methods Apr 15, 2026

Protein foundation models, particularly protein language models, have shown strong success in learning meaningful protein representations using transformer architectures pretrained on large-scale datasets through self-supervised learning. These repre... read more

Lower pre-treatment TMS-evoked cortical reactivity and alpha-band oscillatory dynamics predict efficacy of primary motor cortex neuromodulation for chronic pain.

NeuroImage Apr 15, 2026

Repetitive transcranial magnetic stimulation (rTMS) to the primary motor cortex (M1) provides significant pain relief in ∼45% of chronic pain patients. Identifying biomarkers that predict treatment response before starting rTMS is essential for guidi... read more

AI-enabled autonomous UV-C device pathogen reduction within clinically relevant parameters.

American journal of infection control Apr 15, 2026

Wall-mounted UV-C disinfection systems present a promising alternative to robotic approaches for pathogen reduction. We sought to determine the pathogen-reduction efficacy of such devices when operated at a distance, mimicking real-world applications... read more

Likelihood-free parameter inference for spatiotemporal stochastic biological models using neural posterior estimation.

Journal of theoretical biology Apr 15, 2026

Cell migration is a key biological process underlying wound healing, tissue development, and cancer metastasis, yet calibrating mathematical models of migration to experimental data remains a major challenge. Scratch and barrier assays are widely use... read more

Classification and stratification of patient pain archetypes following total knee arthroplasty: a machine learning approach.

Regional anesthesia and pain medicine Apr 15, 2026

BACKGROUND: Up to 20% of total knee arthroplasty (TKA) patients experience significant postoperative pain that delays recovery and increases risk of chronic pain. Early identification of high-risk patients may allow for timely targeted interventions.... read more

Artificial Intelligence Medical Compendium