AI Medical Compendium

Employee perceptions of AI adoption across service domains in a Finnish public health and social care organization: a cross-sectional mixed-methods study.

BMC health services research Jun 1, 2026

BACKGROUND: Empirical evidence on how employees across different service domains within a single multi-sector public organization perceive AI adoption is limited. This study, therefore, examined differences in self-reported AI usage, perceived compet... read more

Performance comparison of a neuro-symbolic large language model system versus conventional AI models and human experts in cholangitis management.

BMC medical informatics and decision making Jun 1, 2026

BACKGROUND: Large language models (LLMs) have shown promising results in medical decision support; Background: Large language models (LLMs) have demonstrated promising outcomes in medical decision support; however, their efficacy in managing complex ... read more

Breast cancer survival prediction using machine learning and multimodal data for personalized care plan.

BMC cancer Jun 1, 2026

This paper presents a time-stratified breast cancer survival analysis that incorporates tumor characteristics, disease stage, and patient features, using machine learning (ML) algorithms to support personalized care planning. Considering nonlinear re... read more

FSSM-DDI: Fusion State Space Model for predicting drug-drug interaction using social-media and drug descriptions.

BMC biology Jun 1, 2026

BACKGROUND: Predicting drug-drug interactions (DDIs) from social-media and drug descriptions is crucial for healthcare, drug regulation, and pharmaceutical research, yet remains a challenging task. Existing deep learning and Transformer-based approac... read more

Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.

Cardiovascular diabetology Jun 1, 2026

BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed... read more

Landscape of T-cell bispecific antibodies in cancer therapy: therapeutic strategies, challenges and future prospection.

Molecular cancer Jun 1, 2026

T-cell bispecific antibodies (TCBs), a specialized subclass of bispecific antibodies (BsAbs), are engineered to simultaneously engage T cells and tumor cells by binding two distinct antigens-or two epitopes on a single antigen-thereby redirecting cyt... read more

Development and temporal external validation of a high-specificity XGBoost rule-in model for diabetes in middle-aged and older Korean adults.

Diabetology & metabolic syndrome Jun 1, 2026

Early identification of diabetes in older adults is essential for preventing complications, yet many high‑risk individuals remain undetected in community settings. Using recent cycles of the nationally representative Korea National Health and Nutriti... read more

Deep learning-driven decoding of ubiquitination: from regulatory mechanisms to targeted protein degradation.

Biology direct Jun 1, 2026

BACKGROUND: Ubiquitination is a highly dynamic post-translational modification that plays central roles in protein homeostasis, signal transduction, immune regulation, and cell fate control. Through the coordinated actions of E3 ubiquitin ligases and... read more

Development and validation of a machine learning model for predicting distant metastasis in patients with renal cell carcinoma: a population-based study.

World journal of surgical oncology Jun 1, 2026

BACKGROUND: Distant metastasis is the leading cause of death in renal cell carcinoma (RCC), yet accurate prediction tools remain lacking. We aimed to develop and validate a machine learning model to predict synchronous distant metastasis-defined as m... read more

Precision Medicine Gene Network Analyser: part I-cancer driver gene identification through network topology and ensemble machine learning.

Genomics & informatics Jun 1, 2026

PURPOSE: Precision oncology depends on identifying cancer driver genes and linking them to targeted therapies. Current methods using curated gene sets or generic classifiers often miss biologically relevant patterns in complex gene interaction networ... read more

Artificial Intelligence Medical Compendium