AIMC Topic: Artificial Intelligence

Clear Filters Showing 20901 to 20910 of 26332 articles

Is artificial intelligence successful in the Turkish neurology board exam?

Neurological research
OBJECTIVES: OpenAI declared that GPT-4 performed better in academic and certain specialty areas. Medical licensing exams assess the clinical competence of doctors. We aimed to investigate for the first time howChatGPT will perform in the Turkish Neur...

Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography.

Radiology. Artificial intelligence
Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a standard-AI model for diagnosis of intracranial aneurysm. Materials and Methods This retrospective crossover, blinded, multireader, multicase study was co...

Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Artificial Intelligence (AI)-based approaches for extracting Social Drivers of Health (SDoH) from clinical notes offer healthcare systems an efficient way to identify patients' social needs, yet we know little about the acceptability of th...

External Testing of a Commercial AI Algorithm for Breast Cancer Detection at Screening Mammography.

Radiology. Artificial intelligence
Purpose To test a commercial artificial intelligence (AI) system for breast cancer detection at the BC Cancer Breast Screening Program. Materials and Methods In this retrospective study of 136 700 female individuals (mean age, 58.8 years ± 9.4 [SD]; ...

How the National Library of Medicine should evolve in an era of artificial intelligence.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This article describes the challenges faced by the National Library of Medicine with the rise of artificial intelligence (AI) and access to human knowledge through large language models (LLMs).

Mitigation of outcome conflation in predicting patient outcomes using electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Artificial intelligence (AI) models utilizing electronic health record data for disease prediction can enhance risk stratification but may lack specificity, which is crucial for reducing the economic and psychological burdens associated w...

Expectations of healthcare AI and the role of trust: understanding patient views on how AI will impact cost, access, and patient-provider relationships.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Although efforts to effectively govern AI continue to develop, relatively little work has been done to systematically measure and include patient perspectives or expectations of AI in governance. This analysis is designed to understand pa...

Battle of the authors: Comparing neurosurgery articles written by humans and AI.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: The advancement of artificial intelligence (AI) has led to its application in various fields, including medical literature. This study compares the quality of neurosurgery articles written by human authors and those generated by ChatGPT, ...

ChatGPT 4.0 and algor in generating concept maps: an observational study.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: To evaluate the performance of two AI systems, ChatGPT 4.0 and Algor, in generating concept maps from validated otolaryngology clinical practice guidelines.

Advancing periodontal diagnosis: harnessing advanced artificial intelligence for patterns of periodontal bone loss in cone-beam computed tomography.

Dento maxillo facial radiology
OBJECTIVES: The current study aimed to automatically detect tooth presence, tooth numbering, and types of periodontal bone defects from cone-beam CT (CBCT) images using a segmentation method with an advanced artificial intelligence (AI) algorithm.