Abstract Background and Objective Comorbidities, defined as the presence of co-existing
diseases, progress through complex temporal patterns among patients. Learning such …

Objective Routinely collected electronic health records using artificial intelligence (AI)-based
systems bring out enormous benefits for patients, healthcare centers, and its industries …

The broad adoption of electronic health record (EHR) systems brings us a tremendous
amount of clinical data and thus provides opportunities to conduct data-based healthcare …

Background The promise of real-world evidence and the learning health care system
primarily depends on access to high-quality data. Despite widespread awareness of the …

Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that
focuses on individualized patient care by mapping the patient's health information in a …

Introduction: This study aimed to develop novel machine learning models for predicting
Alzheimer's disease (AD) and identify key factors for targeted prevention. Methods: We …

Objective Develop a novel technique to identify an optimal number of regression units
corresponding to a single risk point, while creating risk scoring systems from logistic …

Artificial intelligence is constantly revolutionizing biomedical research and healthcare
management. Disease comorbidity is a major threat to the quality of life for susceptible …

A platform that enables users to schedule appointments and connect with dentists is called
the Dental Services System. The bulk of appointment slot orders are placed through more …

Advancement in Machine Learning (ML) has opened new gateways for transforming the
healthcare sector. This paper explores the integration of ML techniques within the …