The use of chatbot technology, particularly chat generative pre-trained transformer (ChatGPT) with an impressive 175 billion parameters, has garnered significant attention across various domains, including Obstetrics and Gynecology (OBGYN). This comprehensive review delves into the transformative potential of chatbots with a special focus on ChatGPT as a leading artificial intelligence (AI) technology. Moreover, ChatGPT harnesses the power of deep learning algorithms to generate responses that closely mimic human language, opening up myriad applications in medicine, research, and education. In the field of medicine, ChatGPT plays a pivotal role in diagnosis, treatment, and personalized patient education. Notably, the technology has demonstrated remarkable capabilities, surpassing human performance in OBGYN examinations, and delivering highly accurate diagnoses. However, challenges remain, including the need to verify the accuracy of the information and address the ethical considerations and limitations. In the wide scope of chatbot technology, AI systems play a vital role in healthcare processes, including documentation, diagnosis, research, and education. Although promising, the limitations and occasional inaccuracies require validation by healthcare professionals. This review also examined global chatbot adoption in healthcare, emphasizing the need for user awareness to ensure patient safety. Chatbot technology holds great promise in OBGYN and medicine, offering innovative solutions while necessitating responsible integration to ensure patient care and safety.
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http://dx.doi.org/10.5468/ogs.23231 | DOI Listing |
J Korean Med Sci
January 2025
Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Korea.
Background: This study aimed to identify key priorities for the development of guidelines for information and communication technology (ICT)-based patient education tailored to the needs of patients with rheumatic diseases (RDs) in the Republic of Korea, based on expert consensus.
Methods: A two-round modified Delphi study was conducted with 20 rheumatology, patient education, and digital health literacy experts. A total of 35 items covering 7 domains and 18 subdomains were evaluated.
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.
J Autism Dev Disord
January 2025
Department of Public Health Sciences, Clemson University, Clemson, SC, USA.
Youth with autism spectrum disorder (ASD) are at nearly twice the risk of experiencing obesity, compared to youth without ASD. Wellness Education to Create Healthy habits and Actions to Thrive (WE CHAT) is a novel chatbot that engages participants to enhance primary care delivery and associated care coordination services through mobile health (mHealth) technology focused on social determinants of health (SDOH) and social-emotional health. This study examines multiple perspectives regarding the development and implementation of innovative mHealth technology among youth with ASD.
View Article and Find Full Text PDFPart 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dynamic digital representations of patients, offer opportunities for personalized headache management by integrating diverse datasets such as neuroimaging, multiomics, and wearable sensor data to advance headache research, optimize treatment, and enable virtual trials. In addition, AI-driven wearable devices equipped with next-generation biosensors combined with multi-agent chatbots could enable real-time physiological and biochemical monitoring, diagnosing, facilitating early headache attack forecasting and prevention, disease tracking, and personalized interventions.
View Article and Find Full Text PDFSupport Care Cancer
December 2024
Cochrane Taiwan, Taipei Medical University, Taipei, Taiwan.
Background: Effective education and awareness regarding breast cancer are critical. Traditional educational methods often fail to meet the diverse information needs of patients. Patients should be provided with tailored, accessible information to improve their retention and understanding of disease-related information.
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