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Knowledge, Attitudes, Perceptions, and Practices Related to Artificial Intelligence in Radiology Among Indian Radiologists and Residents: A Multicenter Nationwide Study.
Cureus
December 2024
Community and Family Medicine, All India Institute of Medical Sciences, Bhopal, Bhopal, IND.
Background Artificial Intelligence (AI) is revolutionizing medical science, with significant implications for radiology. Understanding the knowledge, attitudes, perspectives, and practices of medical professionals and residents related to AI's role in radiology is crucial for effective integration. Methods A cross-sectional survey was conducted among members of the Indian Radiology & Imaging Association (IRIA), targeting practicing radiologists and residents across academic and non-academic institutions.
View Article and Find Full Text PDFAI-driven multi-omics integration for multi-scale predictive modeling of genotype-environment-phenotype relationships.
Comput Struct Biotechnol J
January 2025
Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, NY, USA.
Despite the wealth of single-cell multi-omics data, it remains challenging to predict the consequences of novel genetic and chemical perturbations in the human body. It requires knowledge of molecular interactions at all biological levels, encompassing disease models and humans. Current machine learning methods primarily establish statistical correlations between genotypes and phenotypes but struggle to identify physiologically significant causal factors, limiting their predictive power.
View Article and Find Full Text PDFA comparison of the persuasiveness of human and ChatGPT generated pro-vaccine messages for HPV.
Front Public Health
January 2025
CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Introduction: Public health messaging is crucial for promoting beneficial health outcomes, and the latest advancements in artificial intelligence offer new opportunities in this field. This study aimed to evaluate the effectiveness of ChatGPT-4 in generating pro-vaccine messages on different topics for Human Papillomavirus (HPV) vaccination.
Methods: In this study ( = 60), we examined the persuasive effect of pro-vaccine messages generated by GPT-4 and humans, which were constructed based on 17 factors impacting HPV vaccination.
Semi-quantitative scoring criteria based on multiple staining methods combined with machine learning to evaluate residual nuclei in decellularized matrix.
Regen Biomater
December 2024
National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, Sichuan 610064, China.
The detection of residual nuclei in decellularized extracellular matrix (dECM) biomaterials is critical for ensuring their quality and biocompatibility. However, current evaluation methods have limitations in addressing impurity interference and providing intelligent analysis. In this study, we utilized four staining techniques-hematoxylin-eosin staining, acetocarmine staining, the Feulgen reaction and 4',6-diamidino-2-phenylindole staining-to detect residual nuclei in dECM biomaterials.
View Article and Find Full Text PDFAutomated Quantitative Assessment of Retinal Vascular Tortuosity in Patients with Sickle Cell Disease.
Ophthalmol Sci
November 2024
Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.
Objective: To quantitatively assess the retinal vascular tortuosity of patients with sickle cell disease (SCD) and retinopathy (SCR) using an automated deep learning (DL)-based pipeline.
Design: Cross-sectional study.
Subjects: Patients diagnosed with SCD and screened for SCR at an academic eye center between January 2015 and November 2022 were identified using electronic health records.
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