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| http://dx.doi.org/10.5534/wjmh.230001 | DOI Listing |
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Assessing the accuracy and quality of artificial intelligence (AI) chatbot-generated responses in making patient-specific drug-therapy and healthcare-related decisions.
BMC Med Inform Decis Mak
December 2024
School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
Background: Interactive artificial intelligence tools such as ChatGPT have gained popularity, yet little is known about their reliability as a reference tool for healthcare-related information for healthcare providers and trainees. The objective of this study was to assess the consistency, quality, and accuracy of the responses generated by ChatGPT on healthcare-related inquiries.
Methods: A total of 18 open-ended questions including six questions in three defined clinical areas (2 each to address "what", "why", and "how", respectively) were submitted to ChatGPT v3.
Publisher Correction: Propagation of errors in citation networks: a study involving the entire citation network of a widely cited paper published in, and later retracted from, the journal Nature.
Res Integr Peer Rev
December 2024
Bioinformatics Laboratory, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands.
A systematic review of whether the number of linguistic errors in medical interpretation is associated with the use of professional vs ad hoc interpreters.
Arch Public Health
December 2024
Department of Forensic Psychiatry, Aarhus University Hospital Psychiatry, Aarhus, Denmark.
Medical consultations depend on a shared linguistic understanding between the patient and physician. When language concordance is not possible, interpretation is required. Prior studies have revealed that professional in-person interpretation (PIPI) results in patients reporting higher satisfaction and a better understanding of things the physician explained.
View Article and Find Full Text PDFInformation Capsule: A New Approach for Summarizing Medical Information.
Int J Prev Med
October 2024
Clinical Informationist Research Group, Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Background: The diversities of medical information resources and health information needs in recent years have caused another form of summarization and abstract writing to appear in the information capsule (IC) versus various types of abstracts. The present study was conducted with the aim to analyze the current IC, giving a unique definition and a standard structure for the development of an IC, and how it can be represented and implemented.
Methods: This study was conducted in three phases in the form of a qualitative study.
Adaptive quantized finite-time fault-tolerant control for uncertain multi-input multi-output systems and its application.
ISA Trans
November 2024
School of Science, University of Science and Technology Liaoning, Anshan Liaoning, 114051, China. Electronic address:
The article proposes a novel state-feedback control method for a multiple-input multiple-output (MIMO) nonlinear system with actuator faults and input quantization. The innovation of the design approach lies in the utilization of fuzzy logic systems (FLSs) to approximate the uncertain intermediate virtual control laws, thereby achieving a simplified virtual control design form. Additionally, finite-time control is employed to enhance the system's response speed.
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