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Evaluation of Generative Artificial Intelligence Models in Predicting Pediatric Emergency Severity Index Levels.
Pediatr Emerg Care
January 2025
University of California Davis School of Medicine, Sacramento, CA.
Objective: Evaluate the accuracy and reliability of various generative artificial intelligence (AI) models (ChatGPT-3.5, ChatGPT-4.0, T5, Llama-2, Mistral-Large, and Claude-3 Opus) in predicting Emergency Severity Index (ESI) levels for pediatric emergency department patients and assess the impact of medically oriented fine-tuning.
View Article and Find Full Text PDFThe PDC30 Chatbot-Development of a Psychoeducational Resource on Dementia Caregiving Among Family Caregivers: Mixed Methods Acceptability Study.
JMIR Aging
January 2025
Department of Computing, Faculty of Computer and Mathematical Sciences, Hong Kong Polytechnic University, Hung Hom, China (Hong Kong).
Background: Providing ongoing support to the increasing number of caregivers as their needs change in the long-term course of dementia is a severe challenge to any health care system. Conversational artificial intelligence (AI) operating 24/7 may help to tackle this problem.
Objective: This study describes the development of a generative AI chatbot-the PDC30 Chatbot-and evaluates its acceptability in a mixed methods study.
Assessing the Severity of Connective Tissue-Related Interstitial Lung Disease Using Computed Tomography Quantitative Analysis Parameters.
J Comput Assist Tomogr
November 2024
From the Department of Medical Imaging, Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin City, Jiangsu Province, China.
Objectives: The aims of the study are to predict lung function impairment in patients with connective tissue disease (CTD)-associated interstitial lung disease (ILD) through computed tomography (CT) quantitative analysis parameters based on CT deep learning model and density threshold method and to assess the severity of the disease in patients with CTD-ILD.
Methods: We retrospectively collected chest high-resolution CT images and pulmonary function test results from 105 patients with CTD-ILD between January 2021 and December 2023 (patients staged according to the gender-age-physiology [GAP] system), including 46 males and 59 females, with a median age of 64 years. Additionally, we selected 80 healthy controls (HCs) with matched sex and age, who showed no abnormalities in their chest high-resolution CT.
Radiofrequency Microneedling in Treating Primary Hyperhidrosis: A Systematic Review and Meta-Analysis.
Dermatol Surg
January 2025
Department of Dermatology, University of Texas Southwestern Medical Center, Dallas, Texas.
Background: Radiofrequency microneedling (RFM) is a potential treatment for primary hyperhidrosis. However, its efficacy is unclear, and treatment parameters and outcomes vary across studies.
Objective: To understand the effect of RFM on treating primary hyperhidrosis, as measured by changes in the Hyperhidrosis Disease Severity Score (HDSS) before and after treatment, and to clearly define treatment settings most likely to optimize results.
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