Cargando…

Stakeholders’ Requirements for Artificial Intelligence for Healthcare in Korea

OBJECTIVES: The outlook of artificial intelligence for healthcare (AI4H) is promising. However, no studies have yet discussed the issues from the perspective of stakeholders in Korea. This research aimed to identify stakeholders’ requirements for AI4H to accelerate the business and research of AI4H....

Descripción completa

Detalles Bibliográficos
Autores principales:	Yu, Jae Yong, Hong, Sungjun, Lee, Yeong Chan, Lee, Kyung Hyun, Lee, Ildong, Seo, Yeoni, Kang, Mira, Kim, Kyunga, Cha, Won Chul, Shin, Soo-Yong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Korean Society of Medical Informatics 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117806/ https://www.ncbi.nlm.nih.gov/pubmed/35576982 http://dx.doi.org/10.4258/hir.2022.28.2.143

Ejemplares similares

Predicting Adverse Outcomes for Febrile Patients in the Emergency Department Using Sparse Laboratory Data: Development of a Time Adaptive Model
por: Lee, Sungjoo, et al.
Publicado: (2020)

Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation Study
por: Hong, Sungjun, et al.
Publicado: (2020)

Artificial intelligence in musculoskeletal ultrasound imaging
por: Shin, YiRang, et al.
Publicado: (2021)

Requirements for Trustworthy Artificial Intelligence and its Application in Healthcare
por: Kim, Myeongju, et al.
Publicado: (2023)

Artificial intelligence using electrocardiography: strengths and pitfalls
por: Kwon, Joon-myoung, et al.
Publicado: (2021)

Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation
por: Chung, Heewon, et al.
Publicado: (2021)

Stakeholders’ views on the organisational factors affecting application of artificial intelligence in healthcare: a scoping review protocol
por: Lebcir, Reda, et al.
Publicado: (2021)

Variability in Doctors’ Usage Paths of Mobile Electronic Health Records Across Specialties: Comprehensive Analysis of Log Data
por: Soh, Ji Yeong, et al.
Publicado: (2019)

Artificial intelligence in healthcare
por: Bohr, Adam, et al.
Publicado: (2020)

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity
por: Baek, Yong-Soo, et al.
Publicado: (2023)

Feasibility of patch-type wireless 12-lead electrocardiogram in laypersons
por: Yoon, Sunyoung, et al.
Publicado: (2023)

Stakeholders’ Perceptions Regarding Digital Therapeutics Reimbursement in South Korea: Qualitative Study
por: Sim, Boram, et al.
Publicado: (2023)

Artificial intelligence in healthcare: past, present and future
por: Jiang, Fei, et al.
Publicado: (2017)

Healthcare Professionals’ Expectations of Medical Artificial Intelligence and Strategies for its Clinical Implementation: A Qualitative Study
por: Yoo, Junsang, et al.
Publicado: (2023)

Intelligence and Stakeholders
por: Walsh, Patrick F.
Publicado: (2018)

Clinical implication of radiographic scores in acute Middle East respiratory syndrome coronavirus pneumonia: Report from a single tertiary-referral center of South Korea
por: Cha, Min Jae, et al.
Publicado: (2018)

Artificial intelligence decision points in an emergency department
por: Chang, Hansol, et al.
Publicado: (2022)

Artificial intelligence for detecting electrolyte imbalance using electrocardiography
por: Kwon, Joon‐myoung, et al.
Publicado: (2021)

Artificial Intelligence for Healthcare in Africa
por: Owoyemi, Ayomide, et al.
Publicado: (2020)

Artificial intelligence in healthcare and education
por: Dave, Manas, et al.
Publicado: (2023)

Artificial Intelligence in Pathology
por: Chang, Hye Yoon, et al.
Publicado: (2019)

Guiding principles for the responsible development of artificial intelligence tools for healthcare
por: Badal, Kimberly, et al.
Publicado: (2023)

Artificial intelligence for predicting five-year survival in stage IV metastatic breast cancer patients: A focus on sarcopenia and other host factors
por: Jang, Woocheol, et al.
Publicado: (2022)

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence
por: Hogg, Henry David Jeffry, et al.
Publicado: (2023)

Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea
por: Lee, Seungseok, et al.
Publicado: (2022)

Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges
por: Lee, DonHee, et al.
Publicado: (2021)

Artificial Intelligence in Health Care: Current Applications and Issues
por: Park, Chan-Woo, et al.
Publicado: (2020)

Artificial intelligence-estimated biological heart age using a 12-lead electrocardiogram predicts mortality and cardiovascular outcomes
por: Baek, Yong-Soo, et al.
Publicado: (2023)

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study
por: Lee, Seungseok, et al.
Publicado: (2023)

Artificial intelligence: applications in healthcare delivery
por: Reddy, Sandeep
Publicado: (2020)

The rise of artificial intelligence in healthcare applications
por: Bohr, Adam, et al.
Publicado: (2020)

Healthcare Transformation in Singapore With Artificial Intelligence
por: Liu, Siqi, et al.
Publicado: (2020)

Artificial Intelligence in Healthcare: Perception and Reality
por: Akinrinmade, Abidemi O, et al.
Publicado: (2023)

Artificial intelligence assessment for early detection and prediction of renal impairment using electrocardiography
por: Kwon, Joon-myoung, et al.
Publicado: (2022)

Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study
por: Jung, Kwang Yul, et al.
Publicado: (2020)

Correction: Frequent Mobile Electronic Medical Records Users Respond More Quickly to Emergency Department Consultation Requests: Retrospective Quantitative Study
por: Jung, Kwang Yul, et al.
Publicado: (2022)

An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome
por: Hur, Sujeong, et al.
Publicado: (2020)

Deep into the Brain: Artificial Intelligence in Stroke Imaging
por: Lee, Eun-Jae, et al.
Publicado: (2017)

Current Management of Type 2 Diabetes Mellitus in Primary Care Clinics in Korea
por: Seo, Da Hea, et al.
Publicado: (2019)

The impact of the COVID-19 pandemic in the healthcare utilization in Korea: Analysis of a nationwide survey
por: Kang, EunKyo, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_gv7koivp36688uuvcvn0fgnkiq