OBJECTIVES: This study aims to develop and validate a novel multimodal interpretable artificial intelligence model capable of fusing radiomics features and imaging features to accurately classify primary central nervous system lymphoma (PCNSL) and gl... read more
BACKGROUND: Artificial Intelligence (AI) is increasingly proposed to enhance population-based cancer screening. While several applications are under evaluation, there is limited evidence on professional and organisational perspectives regarding their... read more
BACKGROUND: This study aimed to develop and internally validate a machine learning-based model for predicting endometrial malignancy, defined as atypical hyperplasia or endometrial cancer (AH/EC), in postmenopausal women, integrating routinely availa... read more
The protein inverse folding problem, which is the task of designing an amino acid sequence that will fold into a specified backbone structure, represents a fundamental challenge in de novo protein design. Existing computational methods, including dee... read more
BACKGROUND: Effective doctor-patient communication is critical in dentistry for diagnostic accuracy and treatment efficacy. Traditional instructional formats afford limited practice opportunities, impeding the transfer of theoretical knowledge to cli... read more
BACKGROUND: Spontaneous bacterial peritonitis (SBP) remains a life-threatening complication of liver cirrhosis, requiring accurate and rapid prediction. Albumin and leukocyte count reflect systemic inflammation and liver dysfunction; combining them i... read more
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
May 26, 2026
This guideline presents Part I of the Canadian Association of Radiologists (CAR) Practice Guidelines on Breast Imaging and Intervention and focuses on mammography and digital breast tomosynthesis (DBT). Developed by the CAR Breast Imaging Working Gro... read more
Computational accounts of learning and decision-making in cognitive systems, and models thereof, such as reinforcement learning, typically assume that the behavior of individual agents is determined by an externally designated reward signal such that... read more
Molecular therapy : the journal of the American Society of Gene Therapy
May 26, 2026
The clinical potential of bispecific T cell engagers (BTEs) is limited by their short serum half-life and the complexity and cost of recombinant protein manufacturing. Currently, BTEs rely on external production and repeat dosing, limiting scalabilit... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.