Background Inflammatory bowel disease (IBD) is a gastrointestinal chronic disease with an
unpredictable disease course. Computational methods such as machine learning (ML) have …

Purpose The development of risk prediction models for breast cancer lymphedema is
increasing, but few studies focus on the quality of the model and its application. Therefore …

Emergency departments (ED) are complex, triage is a main task in the ED to prioritize
patient with limited medical resources who need them most. Machine learning (ML) based …

Objectives De-identifying protected health information (PHI) in medical documents is
important, and a prerequisite to de-identification is the identification of PHI entity names in …

This study aimed to explore the effectiveness of predicting disease activity in patients with
inflammatory bowel disease (IBD), using machine learning (ML) models. A retrospective …

Inflammatory bowel disease (IBD) is a chronic, incurable disease involving the
gastrointestinal tract. It is characterized by complex, unclear pathogenesis, increased …

Background Chronic disease management is a major health issue worldwide. With the
paradigm shift to preventive medicine, disease prediction modeling using machine learning …

Objective: This work aims to systematically identify, describe, and appraise all prognostic
models for cervical cancer and provide a reference for clinical practice and future research …

Background: Inflammatory bowel disease (IBD) is of high medical and socioeconomic
relevance. Moderate and severe disease courses often require treatment with biologics. The …

The surge of artificial intelligence (AI) in medicine stands on a lengthy, and frequently
reticent, buildout. AI is an all-encompassing term for techniques that enable the software to …