AI Medical Compendium

Lancet2: Improved and accelerated somatic variant calling with joint multi-sample local assembly graphs.

NAR genomics and bioinformatics Apr 7, 2026

Here, we present Lancet2, an open-source somatic variant caller designed to improve detection of small variants in short-read sequencing data. Lancet2 introduces significant enhancements, including: (i) Improved variant discovery and genotyping throu... read more

Inspiring the next generation of academic radiologists: A leadership journey.

Current problems in diagnostic radiology Apr 7, 2026

Academic radiology departments in the United States are essential to patient care, education, research, and innovation, yet they face growing challenges such as staffing shortages, rising clinical demands, limited protected academic time, and difficu... read more

Artificial intelligence hallucinations in endodontics: implications for scientific integrity and clinical decision-making.

Restorative dentistry & endodontics Apr 7, 2026

Quantitative susceptibility mapping and MRS-based multimodal machine learning for early Parkinson's disease classification.

NPJ Parkinson's disease Apr 7, 2026

Parkinson's disease (PD) is a complex, progressive neurodegenerative disorder characterized by high heterogeneity and diagnostic challenges in its early stages. This study aimed to develop and validate a multimodal machine learning model for early PD... read more

Adults' dental cone beam computed tomography images dataset for detecting and classifying missing teeth.

Scientific data Apr 7, 2026

The scarcity of high-quality Cone Beam Computed Tomography (CBCT) datasets with Three-Dimensional (3D) annotations hinders advancements in automated dental implant planning. Existing datasets lack precise 3D localization of tooth loss sites, particul... read more

Efficient simulation of optical spectra via machine learning and physical decomposition of environmental effects.

The Journal of chemical physics Apr 7, 2026

Simulations of optical spectra can provide key insights to aid experimental interpretation of electronic excitation phenomena. For chromophores in the condensed phase, these spectra, which incorporate the coupling between electronic excitation and mo... read more

Identifying structural and dynamic features of proteins for machine learning models that predict rates of energy transfer.

The Journal of chemical physics Apr 7, 2026

The flow of vibrational energy in proteins is mediated both by protein structure and structural fluctuations. However, detailed information about contributions of physical properties that mediate energy flow is still lacking. In this report, we prese... read more

Three-Dimensional human motion analysis using LiDAR technology: A systematic review.

Journal of biomechanics Apr 7, 2026

3D Light Detection and Ranging (LiDAR) has gained increasing attention in the field of human motion analysis due to its capability to non-invasively capture dynamic 3D pose data. However, accurate extraction of motion information from sparse and unor... read more

Transforming oncology clinical trial matching through neuro-symbolic, multi-agent AI and an oncology-specific knowledge graph: a prospective evaluation in 3804 patients.

ESMO real world data and digital oncology Apr 7, 2026

BACKGROUND: Clinical trial enrollment in oncology remains critically low, with fewer than 5% of eligible adults participating, in large part due to the complexity and labor intensity of eligibility screening. We prospectively evaluated a neuro-symbol... read more

Investigating fine-tuning versus zero-shot learning for general large language models when predicting cancer survival from initial oncology consultation documents.