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http://dx.doi.org/10.3389/frobt.2021.712521 | DOI Listing |
Cancers (Basel)
January 2025
Center for Precision Health, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
The ICIBM 2023 marked the 11th annual conference of its kind, with the ICIBM recently becoming the official conference of the International Association for Intelligent Biology and Medicine (IAIBM), showcasing cutting-edge advancements at the intersection of computation and biomedical research [...
View Article and Find Full Text PDFBMC Med Genomics
January 2025
The Laboratory of Data Science and Artificial Intelligence Innovation, Department of Computer Science, School of Engineering and Computer Science, Baylor University, Waco, TX, 76798, USA.
Artificial intelligence (AI) is revolutionizing biomedical data science at an unprecedented pace, transforming various aspects of the field with remarkable speed and depth. However, a critical issue remains unclear: how reproducible are the AI models and systems employed in biomedical data science? In this study, we examine the challenges of AI reproducibility by analyzing the factors influenced by data, model, and learning complexities, as well as through a game-theoretical perspective. While adherence to reproducibility standards is essential for the long-term advancement of AI, the conflict between following these standards and aligning with researchers' personal goals remains a significant hurdle in achieving AI reproducibility.
View Article and Find Full Text PDFOphthalmol Ther
January 2025
International Health Policy Program (IHPP), Ministry of Public Health, Nonthaburi, Thailand.
Introduction: Screening diabetic retinopathy (DR) for timely management can reduce global blindness. Many existing DR screening programs worldwide are non-digital, standalone, and deployed with grading retinal photographs by trained personnel. To integrate the screening programs, with or without artificial intelligence (AI), into hospital information systems to improve their effectiveness, the non-digital workflow must be transformed into digital.
View Article and Find Full Text PDFCardiovasc Diagn Ther
December 2024
Department of Heart, Vascular & Thoracic, Division of Cardiology & Cardiovascular Medicine - Pediatric Cardiology, Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA.
As the population of adults with congenital heart disease (ACHD) grows, there also grows an expanded need for non-invasive surveillance methods to guide management and intervention. A multimodal imaging approach layers complementary insights from echocardiography, computed tomography (CT), magnetic resonance imaging (MRI), and other modalities into a clinician's view of patient physiology. Merely applying strategies from acquired adult cardiac disease would be inadequate and potentially misleading.
View Article and Find Full Text PDFCardiovasc Diagn Ther
December 2024
Cardiology, Vascular Medicine & Pneumology, GRN Hospital Weinheim, Weinheim, Germany.
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