Zobrazeno 1 - 10
of 302
pro vyhledávání: '"Won Chul CHA"'
Publikováno v:
Precision and Future Medicine, Vol 8, Iss 3, Pp 92-104 (2024)
Purpose This study aimed to develop real-world synthetic electronic health record (EHR) for emergency departments using computationally efficient and stable diffusion probabilistic models. Methods In this study, we compared the performance of diffusi
Externí odkaz:
https://doaj.org/article/b75f6401e8fc44da84b2875946b44219
Autor:
Sejin Heo, Song-Hee Kim, Se Uk Lee, Sung Yeon Hwang, Hee Yoon, Tae Gun Shin, Hansol Chang, Taerim Kim, Won Chul Cha
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Effective communication between patients and healthcare providers in the emergency department (ED) is challenging due to the dynamic nature of the ED environment. This study aimed to trial a chat service enabling patients in the E
Externí odkaz:
https://doaj.org/article/80e14d0a9a1147f5b494c1d3db69e3a2
Autor:
Namkee Oh, Won Chul Cha, Jun Hyuk Seo, Seong-Gyu Choi, Jong Man Kim, Chi Ryang Chung, Gee Young Suh, Su Yeon Lee, Dong Kyu Oh, Mi Hyeon Park, Chae-Man Lim, Ryoung-Eun Ko
Publikováno v:
Healthcare Informatics Research, Vol 30, Iss 3, Pp 266-276 (2024)
Objectives Sepsis is a leading global cause of mortality, and predicting its outcomes is vital for improving patient care. This study explored the capabilities of ChatGPT, a state-of-the-art natural language processing model, in predicting in-hospita
Externí odkaz:
https://doaj.org/article/4bf82a1ac07e421187e4ae90aeb4eb3e
Autor:
Junhyuk Seo, Dasol Choi, Taerim Kim, Won Chul Cha, Minha Kim, Haanju Yoo, Namkee Oh, YongJin Yi, Kye Hwa Lee, Edward Choi
Publikováno v:
Journal of Medical Internet Research, Vol 26, p e58329 (2024)
BackgroundThe advancement of large language models (LLMs) offers significant opportunities for health care, particularly in the generation of medical documentation. However, challenges related to ensuring the accuracy and reliability of LLM outputs,
Externí odkaz:
https://doaj.org/article/335af22a60ee4f62a44edbbfcb7cbdc2
Autor:
Ji Ye Kang, Weon Jung, Hyun Ji Kim, Ji Hyun An, Hee Yoon, Taerim Kim, Hansol Chang, Sung Yeon Hwang, Jong Eun Park, Gun Tak Lee, Won Chul Cha, Sejin Heo, Se Uk Lee
Publikováno v:
JMIR Public Health and Surveillance, Vol 10, p e59138 (2024)
BackgroundSince its introduction, telemedicine for patients with chronic diseases has been studied in various clinical settings. However, there is limited evidence of the effectiveness and medical safety of the nationwide adoption of telemedicine. O
Externí odkaz:
https://doaj.org/article/f403ab2e9af144dabed04f84d9954673
Autor:
Kyu-Pyo Kim, Kang Mo Kim, Baek-Yeol Ryoo, Won-Mook Choi, Won Chul Cha, Mira Kang, Dong Hyun Sinn, Myung Ji Goh, Do Young Kim, Min Ji Lee, Subin Lim, DongKyu Kim, Kyoungdae Baek, Joohyun Kim, Eui Jun Choi, Doik Lee, Jung-Ae Kim, Ki-Hun Kim
Publikováno v:
Liver Cancer, Pp 1-19 (2024)
Introduction: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality globally, with treatment outcomes closely tied to liver function. This study evaluates the prognostic utility of the albumin-bilirubin (ALBI) score compa
Externí odkaz:
https://doaj.org/article/1aa37e0aefcf496caf8b272eaff7fe77
Autor:
Gun Tak Lee, Daun Jeong, Jong Eun Park, Se Uk Lee, Taerim Kim, Hee Yoon, Won Chul Cha, Min Seob Sim, Ik Joon Jo, Sung Yeon Hwang, Tae Gun Shin
Publikováno v:
Heliyon, Vol 10, Iss 16, Pp e36345- (2024)
Aim: We assessed the efficacy of anti-hyperkalemic agents for alleviating hyperkalemia and improving clinical outcomes in patients with out-of-hospital cardiac arrest (OHCA). Methods: This was a single-center, retrospective observational study of OHC
Externí odkaz:
https://doaj.org/article/e897fac5c0404edb883d348fad1c9e62
Autor:
Jae Yong Yu, Doyeop Kim, Sunyoung Yoon, Taerim Kim, SeJin Heo, Hansol Chang, Gab Soo Han, Kyung Won Jeong, Rae Woong Park, Jun Myung Gwon, Feng Xie, Marcus Eng Hock Ong, Yih Yng Ng, Hyung Joon Joo, Won Chul Cha
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Emergency departments (ED) are complex, triage is a main task in the ED to prioritize patient with limited medical resources who need them most. Machine learning (ML) based ED triage tool, Score for Emergency Risk Prediction (SERP), was prev
Externí odkaz:
https://doaj.org/article/19231b0384ed4715b51b309f4713a949
Publikováno v:
Healthcare Informatics Research, Vol 30, Iss 1, Pp 3-15 (2024)
Objectives Medical artificial intelligence (AI) has recently attracted considerable attention. However, training medical AI models is challenging due to privacy-protection regulations. Among the proposed solutions, federated learning (FL) stands out.
Externí odkaz:
https://doaj.org/article/e098073d0f234b8ab5db69ec594b3b51
Autor:
Shao-An Wang, Chih-Jung Chang, Shan Do Shin, Sheng-En Chu, Chun-Yen Huang, Li-Min Hsu, Hao-Yang Lin, Ki Jeong Hong, Sabariah Faizah Jamaluddin, Do Ngoc Son, T.V. Ramakrishnan, Wen-Chu Chiang, Jen-Tang Sun, Matthew Huei-Ming Ma, Participating Nation Investigators, Hideharu Tanaka, Bernadett Velasco, Jen Tang Sun, Pairoj Khruekarnchana, Saleh Fares, Participating Site Investigators, Ramana Rao, George P. Abraham, Mohd Amin Bin Mohidin, Al-Hilmi Saim, Lim Chee Kean, Cecilia Anthonysamy, Shah Jahan Din Mohd Yssof, Kang Wen Ji, Cheah Phee Kheng, Shamila bt Mohamad Ali, Periyanayaki Ramanathan, Chia Boon Yang, Hon Woei Chia, Hafidahwati Binti Hamad, Samsu Ambia Ismail, Wan Rasydan B. Wan Abdullah, Akio Kimura, Carlos D. Gundran, Pauline Convocar, Nerissa G. Sabarre, Patrick Joseph Tiglao, Kyoung Jun Song, Joo Jeong, Sung Woo Moon, Joo-yeong Kim, Won Chul Cha, Seung Chul Lee, Jae Yun Ahn, Kang Hyeon Lee, Seok Ran Yeom, Hyeon Ho Ryu, Su Jin Kim, Sang Chul Kim, Ray-Heng Hu, Ruei-Fang Wang, Shang-Lin Hsieh, Wei-Fong Kao, Sattha Riyapan, Parinya Tianwibool, Phudit Buaprasert, Osaree Akaraborworn, Omer Ahmed Al Sakaf, Le Bao Huy, Nguyen Van Dai
Publikováno v:
Journal of the Formosan Medical Association, Vol 123, Iss 1, Pp 23-35 (2024)
Background/Purpose: To develop a prediction model for emergency medical technicians (EMTs) to identify trauma patients at high risk of deterioration to emergency medical service (EMS)-witnessed traumatic cardiac arrest (TCA) on the scene or en route.
Externí odkaz:
https://doaj.org/article/e816f56b76be43749e3588bef558d286