Prevention of medical errors

Identifying potential ligand-receptor interactions by integrating LSTM network and the attention mechanism for cell-cell communication prediction.

BACKGROUND: Cell-cell communication (CCC) mediated by ligand-receptor (L-R) interactions is fundamental to deciphering tissue development and disease mechanisms. While single-cell RNA sequencing (scRNA-seq) has advanced this field, existing computational methods for inferring CCC often suffer from limitations such as dependence on static databases and a failure to capture the sequential dependency...

Artematrolide F suppresses communication between hepatocellular carcinoma cells and hepatic stellate cells to attenuate liver cancer progression through targeting YKT6.

Hepatocellular carcinoma (HCC) remains a highly malignant cancer with limited treatment options. HCC cells (HCCs) activate hepatic stellate cells (HSCs) and transform them into cancer-associated fibroblasts (CAFs), forming a vicious cycle for hepatocarcinogenesis. Therefore, inhibition of the communication between HCCs and HSCs is expected to emerge as a novel strategy for HCC treatment. Artematro...

Parallel AI-driven framework for post-quantum secure medical image communication using swin-transformer restoration.

Reliable and secure transmission of medical images is essential for telemedicine, remote diagnosis, and distributed healthcare systems. However, medic...

Beyond readability: Advancing patient-centered evaluation of AI-generated clinical reports.

Large language models offer promising opportunities to simplify clinical documentation and improve the accessibility of medical information for patien...

Advancing One Health: Innovations and Future Directions in Mycotoxin Detection, Management, and Prevention-Narrative Review.

Mycotoxins, toxic secondary metabolites generated by fungi such as Aspergillus, Fusarium, and Penicillium species pose substantial concerns to food sa...

Preoperative Risk Assessment of Adrenal Metastases in a Multicenter Study: Development of a Robust Federated Learning Model.

RATIONALE AND OBJECTIVES: In clinical practice, the preoperative risk assessment of adrenal metastases versus benign adrenal lesions carries a substan...

When the Algorithm Speaks: A Case for Simulation-Based Training in Communicating Artificial Intelligence-Generated Prognostic Outputs in Oncology.

Artificial intelligence prognostic tools are now embedded in routine oncology workflows, generating recurrence risk scores and survival estimates that...

Machine Learning Applications Within the Earlier Medicine Framework for Stroke: A Scoping Review.

This scoping review explores how machine learning (ML) has been applied to stroke research within the Earlier Medicine framework, which promotes proac...

PROSODIC: Predictive Intelligence for Secondary Prevention of Youth Suicide.

Suicide is currently the leading cause of preventable death among young people, yet early identification of reattempt risk remains limited by its mult...

Factors Associated with the Acceptance of Communication Robots Among Formal Caregivers in Home-Based Care.

We investigated factors associated with the acceptance of communication robots among formal caregivers in home care. A cross-sectional survey conducte...

A Human-Centered, Multi-Stage Clinical Decision Pathway for an AI-Based CDSS for Delirium Prevention.

Delirium is common, consequential, and in many cases preventable in acute care. Building on participatory work with healthcare professionals (HCP), we...

Feasibility of LLM-Assisted Communication Feedback in Simulation-Based Medical Education: A Pilot Study.

The study presents a local large language model pipeline for automated feedback in pediatric simulation-based medical education. The system generates ...

ASO Special Article: Proceedings of the Inaugural Joint US-India Cancer Dialogue: Accelerating Collaboration to Advance Cancer Prevention, Early Detection, Treatment, and Care.

BACKGROUND: Cancer is a leading cause of death in both the USA and India. During Prime Minister Narendra Modi's State Visit to Washington, DC in June ...

Japanese-Language AI Agent System for Human Papillomavirus Vaccine Infoveillance and Public Communication: Development and Feasibility Evaluation.

BACKGROUND: Human papillomavirus (HPV) vaccine hesitancy remains a significant public health challenge in Japan, where proactive vaccination recommend...

A V2X communication resource allocation method based on graph neural networks and deep reinforcement learning.

High frequency vehicle-to-vehicle (V2V) communication in the Internet of Vehicles (IoV) leads to severe spectrum collisions and limited system capacit...

Content matters, context matters: unraveling behavior dynamics in an online health community for tobacco cessation.

OBJECTIVES: The objective of this research was to examine the content and context-specific information diffusion patterns underlying communication per...

A long-term image-derived AI-based risk model for primary prevention of breast cancer in individuals at high risk.

Image-derived artificial intelligence (AI) risk models have shown promise in short-term risk assessment for improving breast cancer (BC) screening. No...

Revealing the Latent Structure of Health Literacy in Online Peer-to-Peer Communication with Uncertainty-aware Bayesian Deep Learning.

Health literacy is a multidimensional construct essential for health decision-making, yet its computational assessment from naturalistic online discou...

Precision nutrition for the prevention and management of inflammatory bowel disease.

The rising disease burden of inflammatory bowel disease (IBD) parallels the changing dietary landscape accompanying industrialization, underscoring th...

Artificial intelligence for assessment in competency-based medical education: current practices and future directions.

BACKGROUND: Competency-Based Medical Education (CBME) relies on frequent, competency-focused assessments, which can be challenging to implement consis...