The issue of medical errors is currently a global concern which places a heavy financial and emotional burden on communities. A clinical decision support system (CDSS) is an electronic system designed to support clinical decision making. Considering the increasing importance and use of Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), we developed SNOMED-CT to implement it more efficiently in making smart history taking, decisions to perform lab tests and imaging, diagnosis and recommendations. To evaluate these capabilities in real clinical problems, a new CDSS was compiled, aimed at supporting decisions on patients with a chief complaint of low back pain (LBP). A number of LBP differential diagnoses as well as some recommended indications and contraindications published by guidelines, were inputted to the database. Future software based on this model would help physicians to do necessary assessments and recommendations and might improve patients' safety.
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Proc Natl Acad Sci U S A
January 2025
Department of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125.
Cognition relies on transforming sensory inputs into a generalizable understanding of the world. Mirror neurons have been proposed to underlie this process, mapping visual representations of others' actions and sensations onto neurons that mediate our own, providing a conduit for understanding. However, this theory has limitations.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Institute of Data Science, National University of Singapore, 117602, Singapore.
Objectives: This study introduces Smart Imitator (SI), a 2-phase reinforcement learning (RL) solution enhancing personalized treatment policies in healthcare, addressing challenges from imperfect clinician data and complex environments.
Materials And Methods: Smart Imitator's first phase uses adversarial cooperative imitation learning with a novel sample selection schema to categorize clinician policies from optimal to nonoptimal. The second phase creates a parameterized reward function to guide the learning of superior treatment policies through RL.
Otol Neurotol
February 2025
Department of Radiology, Yale School of Medicine, New Haven, CT.
Background: Vestibular schwannoma (VS) is a common intracranial tumor that affects patients' quality of life. Reliable imaging techniques for tumor volume assessment are essential for guiding management decisions. The study aimed to compare the ABC/2 method to the gold standard planimetry method for volumetric assessment of VS.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Cardiovascular Medicine, Chiba University Graduate School of Medicine, Chiba, Japan.
Background: Training opportunities, work satisfaction, and the factors that influence them according to gender and subspecialties are understudied among Japanese cardiologists.
Methods: We investigated the career development of Japanese cardiologists with an e-mail questionnaire. Feelings of inequality in training opportunities, work dissatisfaction, and reasons were assessed by examining the cardiologists' gender and invasiveness of subspecialties.
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