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Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Extracting seizure control metrics from clinic notes of patients with epilepsy: A natural language processing approach.

OBJECTIVES: Monitoring seizure control metrics is key to clinical care of patients with epilepsy. Ma...

6G in medical robotics: development of network allocation strategies for a telerobotic examination system.

PURPOSE: Healthcare systems around the world are increasingly facing severe challenges due to proble...

Integrating AI with tele-ophthalmology in Canada: a review.

The field of ophthalmology is rapidly advancing, with technological innovations enhancing the diagno...

Artificial intelligence and telemedicine in epilepsy and EEG: A narrative review.

The emergence of telemedicine and artificial intelligence (AI) has set the stage for a possible revo...

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...

An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology.

Automatic disease progression prediction models require large amounts of training data, which are se...

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...

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 ...

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...

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...

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...

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