AIMC Topic: Medical Informatics

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Incorporating Generative AI Into a Health Informatics Curriculum to Build 21st Century Competencies: Multisite Pre-Post Study.

JMIR medical informatics
BACKGROUND: We designed learning assignments for students to develop knowledge, skills, and professional attitudes about generative artificial intelligence (AI) in 2 different Master's level courses in health informatics. Our innovative approach assu...

Acceptability of Health Information Technology by Health Care Professionals: Where We Are Now and How We Can Fill the Gap.

Journal of medical Internet research
Digital health is expected to improve the efficiency and quality of health. Health information technologies (HIT) imply allocated time, appropriate training, and new types of responsibility, whose physical and mental impact on health care professiona...

Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study.

BMC medical education
BACKGROUND: Large language models (LLMs) like ChatGPT offer new ways to improve academic and administrative workflows in medical education, particularly for students studying in a language that is not their native tongue. We set out to examine whethe...

MedKA: A knowledge graph-augmented approach to improve factuality in medical Large Language Models.

Journal of biomedical informatics
Large language models (LLMs) have demonstrated remarkable potential in medical applications. However, they still face critical challenges such as hallucinations, knowledge inconsistency, and insufficient integration of domain-specific medical experti...

Leveraging heterogeneous tabular of EHRs with prompt learning for clinical prediction.

Journal of biomedical informatics
Electronic Health Records (EHRs) depict patient-related information and have significantly contributed to advancements in healthcare fields. The abundance of EHR data provides exceptional opportunities for developing clinical predictive models. Howev...

Integrating an AI platform into clinical IT: BPMN processes for clinical AI model development.

BMC medical informatics and decision making
BACKGROUND: There has been a resurgence of Artificial Intelligence (AI) on a global scale in recent times, resulting in the development of cutting-edge AI solutions within hospitals. However, this has also led to the creation of isolated AI solutions...

Data-driven trends in critical care informatics: a bibliometric analysis of global collaborations using the MIMIC database (2004-2024).

Computers in biology and medicine
BACKGROUND: The Medical Information Mart for Intensive Care (MIMIC) database has become a cornerstone resource for critical care research, enabling advances in outcome prediction, machine learning, and patient management. However, comprehensive bibli...

GatorCLR: Personalized predictions of patient outcomes on electronic health records using self-supervised contrastive graph representation.

Journal of biomedical informatics
OBJECTIVE: Recently, there has been growing interest in analyzing large amounts of Electronic Health Record (EHR) data. Patient outcome prediction is a major area of interest in EHR analysis that focuses on predicting the future health status of pati...

Leveraging Hospital Information Data for Effective Antibiotic Stewardship.

Journal of Korean medical science
Clinical informatics has emerged as a valuable approach to enhance antimicrobial stewardship programs in healthcare settings. By integrating information technology with healthcare services, hospitals can systematically collect, store, and utilize med...

Anomaly Detection in Electronic Health Records Across Hospital Networks: Integrating Machine Learning With Graph Algorithms.

IEEE journal of biomedical and health informatics
In a large hospital system, a network of hospitals relies on electronic health records (EHRs) to make informed decisions regarding their patients in various clinical domains. Consequently, the dependability of the health information technology (HIT) ...