Patient Education and Counseling, Год журнала: 2025, Номер unknown, С. 108746 - 108746
Опубликована: Март 1, 2025
Язык: Английский
Frontiers in Artificial Intelligence, Год журнала: 2023, Номер 6
Опубликована: Окт. 31, 2023
The release of ChatGPT has initiated new thinking about AI-based Chatbot and its application drawn huge public attention worldwide. Researchers doctors have started the promise AI-related large language models in medicine during past few months. Here, comprehensive review highlighted overview their current role medicine. Firstly, general idea Chatbots, evolution, architecture, medical use are discussed. Secondly, is discussed with special emphasis medicine, architecture training methods, diagnosis treatment, research ethical issues, a comparison other NLP illustrated. article also limitations prospects ChatGPT. In future, these will immense healthcare. However, more needed this direction.
Язык: Английский
Процитировано
65
Interactive Technology and Smart Education, Год журнала: 2023, Номер 21(2), С. 189 - 213
Опубликована: Март 27, 2023
Purpose The application of artificial intelligence chatbots is an emerging trend in educational technology studies for its multi-faceted advantages. However, the existing rarely take a perspective to evaluate contexts. This study aims bridge research gap by taking review literature on chatbots. Design/methodology/approach combines bibliometric analysis and citation network analysis: through visualization keyword, authors, organizations countries based clustering. Findings Educational applications are still rising post-COVID-19 learning environments. Popular issues this topic include technological advancements, students’ perception effectiveness different Originating from similar theoretical foundations, primarily applied language education, services (such as information counseling automated grading), health-care education medical training. Diversifying contexts demonstrate specific purposes using but confronted with some common challenges. Multi-faceted factors can influence acceptance education. provides extended framework facilitate extending chatbot Research limitations/implications authors have acknowledge that subjected limitations. First, search was core collection Web Science, which did not studies. Second, only included published English. Third, due limitation expertise, could comprehensively interpret implications reporting advancements. intended establish significance summarizing evaluating perspective. Originality/value identifies publication trends It bridges caused previous neglection treating interconnected whole characteristics. major encouraged further applications. also proposes consider covers three critical components integration when future researchers instructors apply new
Язык: Английский
Процитировано
57
JAMA Oncology, Год журнала: 2024, Номер 10(7), С. 956 - 956
Опубликована: Май 16, 2024
Artificial intelligence (AI) chatbots pose the opportunity to draft template responses patient questions. However, ability of generate based on domain-specific knowledge cancer remains be tested.
Язык: Английский
Процитировано
35
Journal of Genetic Counseling, Год журнала: 2022, Номер 31(5), С. 1219 - 1230
Опубликована: Май 26, 2022
Abstract Successful proband‐mediated family communication and subsequent cascade genetic testing uptake requires interventions that present information clearly, in sufficient detail, with medical authority. To facilitate for patients receiving clinically actionable results via the MyCode® Community Health Initiative, a Family Sharing Tool (FST) chatbot were developed. FST is an electronic mechanism allowing to share test relatives chatbot. The describes proband's result, associated disease risks, recommended management captures whether user blood relative or caregiver, sex, relationship proband. among probands was tracked from August 2018 through February 2020. Cascade collected laboratories as number of cascades per Fifty‐eight percent (316/543) consented FST; 42% (227/543) declined. Receipt preferences patient health record (EHR) portal (52%), email (29%), text (19%). Patient EHR users ( p < 0.001) younger more likely consent 0.001). deployed 308 probands. Fifty‐nine (183/308) opened; those, 56% (102/183) used send relatives. These 102 shared 377 Sixty‐two (235/377) these, 69% (161/235) started, 57% (92/161) completed significantly greater who M = 2.34 cascades, SD 2.10) than declined 1.40 0.82, Proband age not significant predictor uptake. Further work needed better understand factors impacting proband use chatbots.
Язык: Английский
Процитировано
48
International Journal of General Medicine, Год журнала: 2023, Номер Volume 16, С. 1591 - 1602
Опубликована: Май 1, 2023
Background: Few reports have investigated chatbots in patient care. We aimed to assess the current applications, limitations, and challenges literature on employed oncological Methods: queried PubMed database through April 2022 included studies that use of different phases The search used five combinations specific terms "chatbot", "cancer", "oncology", "conversational agent". Inclusion criteria were chatbot any aspect care—prevention, education, treatment, surveillance. Results: initial yielded 196 records, 21 which met inclusion criteria. identified mostly focused breast ovarian cancer (n=8), with second most common being cervical (n=3). Good satisfaction was reported among 14 chatbots. applications screening, prevention, risk stratification, monitoring, management. Of 12 examining efficacy care via chatbot, 9 demonstrated improvements compared standard Conclusion: Chatbots for date demonstrate high user satisfaction, many shown improving patient-centered communication, accessibility cancer-related information, access Currently, are primarily limited by need extensive user-testing iterative improvement before widespread implementation. Keywords: conversational agent, artificial intelligence, AI, cancer, oncology
Язык: Английский
Процитировано
39
American Journal of Medical Genetics Part C Seminars in Medical Genetics, Год журнала: 2023, Номер 193(3)
Опубликована: Июль 28, 2023
Abstract The transition from analog to digital technologies in clinical laboratory genomics is ushering an era of “big data” ways that will exceed human capacity rapidly and reproducibly analyze those data using conventional approaches. Accurately evaluating complex molecular facilitate timely diagnosis management genomic disorders require supportive artificial intelligence methods. These are already being introduced into identify variants DNA sequencing data, predict the effects on protein structure function inform interpretation pathogenicity, link phenotype ontologies genetic identified through exome or genome help clinicians reach diagnostic answers faster, correlate with tumor staging treatment approaches, utilize natural language processing critical published medical literature during analysis use interactive chatbots individuals who qualify for testing provide pre‐test post‐test education. With careful ethical development validation genomics, these advances expected significantly enhance abilities geneticists translate clearly synthesized information managing care their patients at scale.
Язык: Английский
Процитировано
29
Journal of the American Medical Informatics Association, Год журнала: 2024, Номер 31(10), С. 2271 - 2283
Опубликована: Июнь 14, 2024
To evaluate the efficacy of ChatGPT 4 (GPT-4) in delivering genetic information about BRCA1, HFE, and MLH1, building on previous findings with 3.5 (GPT-3.5). focus assessing utility, limitations, ethical implications using medical settings.
Язык: Английский
Процитировано
16
Universal Access in the Information Society, Год журнала: 2024, Номер unknown
Опубликована: Май 10, 2024
Abstract Healthcare is one of the most important sectors our society, and during COVID-19 pandemic a new challenge emerged—how to support people safely effectively at home regarding their health-related problems. In this regard chatbots or conversational agents (CAs) play an increasingly role, are spreading rapidly. They can enhance not only user interaction by delivering quick feedback responses, but also hospital management, thanks several features. Considerable research focused on making CAs more reliable, accurate, robust. However, critical aspect how make them inclusive, in order users unfamiliar with technology, such as elderly disabilities. study, we investigate current use healthcare, exploring evolution over time inclusivity. The study was carried out four digital libraries (ScienceDirect, IEEE Xplore, ACM Digital Library, Google Scholar) articles published last 5 years, total 21 describing implemented actually used eHealth clinical area. results showed notable improvement few years highlight some design issues, including poor attention inclusion. Based findings, recommend different kind approach for implementing inclusive accessibility-by-design approach.
Язык: Английский
Процитировано
10
Enterprise Information Systems, Год журнала: 2025, Номер unknown
Опубликована: Фев. 25, 2025
Язык: Английский
Процитировано
1
Current Oncology, Год журнала: 2025, Номер 32(3), С. 145 - 145
Опубликована: Март 2, 2025
The Artificial Intelligence Patient Librarian (AIPL) was designed to meet the psychosocial and supportive care needs of Metastatic Breast Cancer (MBC) patients with HR+/HER2− subtypes. AIPL provides conversational patient education, answers user questions, offers tailored online resource recommendations. This study, conducted in three phases, assessed AIPL’s impact on patients’ ability manage their advanced disease. In Phase 1, educational content adapted for chatbot delivery, over 100 credible resources were annotated using a Convolutional Neural Network (CNN) drive 2 involved 42 participants who completed pre- post-surveys after two weeks. surveys measured activation Activation Measure (PAM) tool evaluated experience System Usability Scale (SUS). 3 included focus groups explore experiences depth. Of participants, 36 10 participating groups. Most aged 40–64. PAM scores showed no significant differences between pre-survey (mean = 59.33, SD 5.19) post-survey 59.22, 6.16), while SUS indicated good usability. Thematic analysis revealed four key themes: basic wellness health guidance, limited support managing relationships, condition-specific medical information, is unable offer hope patients. Despite showing PAM, possibly due high baseline activation, demonstrated usability met information needs, particularly newly diagnosed MBC Future iterations will incorporate large language model (LLM) provide more comprehensive personalized assistance.
Язык: Английский
Процитировано
1