AI Medical Compendium

Artificial intelligence in paediatric neuroradiology: current landscape, challenges, and future directions.

Pediatric radiology Feb 23, 2026

This narrative review maps the current landscape of artificial intelligence (AI) in paediatric and fetal neuroradiology, critically evaluating current practice, barriers to clinical adoption, and future potential. We searched for peer-reviewed studie... read more

Deep learning-based automated positioning system for maxillary skeletal expander: development and clinical validation.

Clinical oral investigations Feb 23, 2026

Brain organoids in environmental neurotoxicology: applications, mechanisms, and future perspectives.

Cell biology and toxicology Feb 23, 2026

The advent of human induced pluripotent stem cell (hiPSC)-derived brain organoids represents a significant advance in environmental neurotoxicology, propelling the discipline toward human-relevant, mechanistic, and predictive in vitro paradigms. This... read more

Can AI write reports like a radiologist? A blinded evaluation of large language model-generated lumbar spine MRI reports.

European radiology experimental Feb 23, 2026

BACKGROUND: To compare the quality and clinical usefulness of large language model (LLM)-generated lumbar spine magnetic resonance imaging (MRI) reports with radiologist-written ones and assess whether medical professionals can distinguish between th... read more

Deep learning pipeline for trapezium segmentation in thumb radiographs.

European radiology experimental Feb 23, 2026

OBJECTIVE: Accurate identification of the trapezium is crucial for trapeziometacarpal (TMC) arthroplasty but remains challenging on standard radiographs due to overlapping anatomy. Artificial intelligence has shown promise in musculoskeletal imaging,... read more

Artificial intelligence in concrete mix design: a comprehensive review.

Environmental science and pollution research international Feb 23, 2026

Concrete mix design plays a vital role in achieving the desired mechanical and durability properties of concrete while optimizing material use and cost. Traditional design methods often rely on empirical formulas and multiple laboratory trials, makin... read more

Machine learning to design metal-organic frameworks: progress and challenges from a data efficiency perspective.

Materials horizons Feb 23, 2026

This review critically examines work at the intersection of machine learning (ML) and metal-organic frameworks (MOFs). The modular nature of MOFs enables immense design flexibility and applicability to a wide range of applications. However, the combi... read more

The carbon cost of materials discovery: Can machine learning really accelerate the discovery of new photovoltaics?

Materials horizons Feb 23, 2026

Computational screening has become a powerful complement to experimental efforts in the discovery of high-performance photovoltaic (PV) materials. Most workflows rely on density functional theory (DFT) to estimate electronic and optical properties re... read more

Content-state-driven motility switching in an intestine-inspired soft-bodied robot via decentralised oscillator networks.

Bioinspiration & biomimetics Feb 23, 2026

Adaptive handling of thick or composition-changing fluids is difficult for conventional pumps. In animals, the intestine addresses this challenge by switching between segmental mixing and peristaltic transport according to the physical state of the c... read more

Evaluation of the impact of NOAC underdosing and exploration of bleeding risk factors in elderly patients with atrial fibrillation: artificial intelligence-based approach.

European journal of hospital pharmacy : science and practice Feb 23, 2026

OBJECTIVE: Atrial fibrillation in elderly patients increases the risk of thromboembolism, necessitating long-term anticoagulation. While non-vitamin K oral anticoagulants (NOACs) are generally preferred, appropriate dosing in older patients who are f... read more

Artificial Intelligence Medical Compendium