Information Technology

Special supplement issue on quality assurance and enrichment of biological and biomedical ontologies and terminologies.

Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains...

Cybersecurity in the generative artificial intelligence era.

Generative Artificial Intelligence (GenAI) are algorithms capable of generating original content. Th...

A neural network approach to predict opioid misuse among previously hospitalized patients using electronic health records.

Can Electronic Health Records (EHR) predict opioid misuse in general patient populations? This resea...

Task sharing for increasing access to obstetric ultrasonography: a formative qualitative study of nurse-led scanning with telemedicine review in Kenya.

The informal settlements of Nairobi have higher neonatal and infant mortality rates than the average...

How artificial intelligence is transforming nephrology.

Current research in nephrology is increasingly focused on elucidating the complexity inherent in tig...

Informatics-driven solutions for optimal care delivery in liver transplantation.

Clinical informatics, which combines health information technology and clinical expertise, aims to i...

Digital health in stroke: a narrative review.

Digital health is significantly transforming stroke care, particularly in remote and economically di...

Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges.

A large language model (LLM) is an artificial intelligence (AI) model that uses natural language pro...

The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to un...

Multi-task heterogeneous graph learning on electronic health records.

Learning electronic health records (EHRs) has received emerging attention because of its capability ...

Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study.

BACKGROUND: Accurate patient outcome prediction in the intensive care unit (ICU) can potentially lea...

Innovation and challenges of artificial intelligence technology in personalized healthcare.

As the burgeoning field of Artificial Intelligence (AI) continues to permeate the fabric of healthca...

Technological Advances in the Diagnosis of Cardiovascular Disease: A Public Health Strategy.

This article reviews technological advances and global trends in the diagnosis, treatment, and monit...

Metabolic dysfunctions predict the development of Alzheimer's disease: Statistical and machine learning analysis of EMR data.

INTRODUCTION: The incidence of Alzheimer's disease (AD) and obesity rise concomitantly. This study e...

Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension.

INTRODUCTION: There are limited data available regarding the connection between heavy metal exposure...

Artificial Intelligence-Based Digital Biomarkers for Type 2 Diabetes: A Review.

Type 2 diabetes mellitus (T2DM), a complex metabolic disorder that burdens the health care system, r...

The revolution of metaverse in surgery: a mini-review with video.

The virtual reality (VR) is an application in which people can interact each other with their own av...

Machine learning characterization of a rare neurologic disease via electronic health records: a proof-of-principle study on stiff person syndrome.

BACKGROUND: Despite the frequent diagnostic delays of rare neurologic diseases (RND), it remains dif...

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

BACKGROUND: Efforts are underway to capitalize on the computational power of the data collected in e...

Innovative approaches in stroke care: insights from recent studies on patient delay, telemedicine, artificial intelligence, and machine learning.

Multimodal deep learning models utilizing chest X-ray and electronic health record data for predictive screening of acute heart failure in emergency department.

BACKGROUND AND OBJECTIVES: Ambiguity in diagnosing acute heart failure (AHF) leads to inappropriate ...