Zobrazeno 1 - 10
of 172
pro vyhledávání: '"ONG, JASMINE"'
Autor:
Ke, Yu He, Jin, Liyuan, Elangovan, Kabilan, Abdullah, Hairil Rizal, Liu, Nan, Sia, Alex Tiong Heng, Soh, Chai Rick, Tung, Joshua Yi Min, Ong, Jasmine Chiat Ling, Kuo, Chang-Fu, Wu, Shao-Chun, Kovacheva, Vesela P., Ting, Daniel Shu Wei
Large Language Models (LLMs) show potential for medical applications but often lack specialized clinical knowledge. Retrieval Augmented Generation (RAG) allows customization with domain-specific information, making it suitable for healthcare. This st
Externí odkaz:
http://arxiv.org/abs/2410.08431
Autor:
Tan, Ting Fang, Elangovan, Kabilan, Ong, Jasmine, Shah, Nigam, Sung, Joseph, Wong, Tien Yin, Xue, Lan, Liu, Nan, Wang, Haibo, Kuo, Chang Fu, Chesterman, Simon, Yeong, Zee Kin, Ting, Daniel SW
A comprehensive qualitative evaluation framework for large language models (LLM) in healthcare that expands beyond traditional accuracy and quantitative metrics needed. We propose 5 key aspects for evaluation of LLMs: Safety, Consensus, Objectivity,
Externí odkaz:
http://arxiv.org/abs/2407.07666
Autor:
Elangovan, Kabilan, Ong, Jasmine Chiat Ling, Jin, Liyuan, Seng, Benjamin Jun Jie, Kwan, Yu Heng, Tan, Lit Soo, Zhong, Ryan Jian, Ma, Justina Koi Li, Ke, YuHe, Liu, Nan, Giacomini, Kathleen M, Ting, Daniel Shu Wei
Large Language Models (LLMs) have emerged as a potential solution to assist digital health development with patient education, commonly medication-related enquires. We trained and validated Med-Pal, a medication domain-specific LLM-chatbot fine-tuned
Externí odkaz:
http://arxiv.org/abs/2407.12822
Autor:
Yang, Rui, Ning, Yilin, Keppo, Emilia, Liu, Mingxuan, Hong, Chuan, Bitterman, Danielle S, Ong, Jasmine Chiat Ling, Ting, Daniel Shu Wei, Liu, Nan
Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling mode
Externí odkaz:
http://arxiv.org/abs/2406.12449
Autor:
Liu, Mingxuan, Ning, Yilin, Teixayavong, Salinelat, Liu, Xiaoxuan, Mertens, Mayli, Shang, Yuqing, Li, Xin, Miao, Di, Xu, Jie, Ting, Daniel Shu Wei, Cheng, Lionel Tim-Ee, Ong, Jasmine Chiat Ling, Teo, Zhen Ling, Tan, Ting Fang, RaviChandran, Narrendar, Wang, Fei, Celi, Leo Anthony, Ong, Marcus Eng Hock, Liu, Nan
The ethical integration of Artificial Intelligence (AI) in healthcare necessitates addressing fairness-a concept that is highly context-specific across medical fields. Extensive studies have been conducted to expand the technical components of AI fai
Externí odkaz:
http://arxiv.org/abs/2405.17921
Autor:
Ong, Jasmine Chiat Ling, Jin, Liyuan, Elangovan, Kabilan, Lim, Gilbert Yong San, Lim, Daniel Yan Zheng, Sng, Gerald Gui Ren, Ke, Yuhe, Tung, Joshua Yi Min, Zhong, Ryan Jian, Koh, Christopher Ming Yao, Lee, Keane Zhi Hao, Chen, Xiang, Chng, Jack Kian, Than, Aung, Goh, Ken Junyang, Ting, Daniel Shu Wei
Importance: We introduce a novel Retrieval Augmented Generation (RAG)-Large Language Model (LLM) framework as a Clinical Decision Support Systems (CDSS) to support safe medication prescription. Objective: To evaluate the efficacy of LLM-based CDSS in
Externí odkaz:
http://arxiv.org/abs/2402.01741
Autor:
Ke, YuHe, Jin, Liyuan, Elangovan, Kabilan, Abdullah, Hairil Rizal, Liu, Nan, Sia, Alex Tiong Heng, Soh, Chai Rick, Tung, Joshua Yi Min, Ong, Jasmine Chiat Ling, Ting, Daniel Shu Wei
Purpose: Large Language Models (LLMs) hold significant promise for medical applications. Retrieval Augmented Generation (RAG) emerges as a promising approach for customizing domain knowledge in LLMs. This case study presents the development and evalu
Externí odkaz:
http://arxiv.org/abs/2402.01733
Autor:
Ning, Yilin, Teixayavong, Salinelat, Shang, Yuqing, Savulescu, Julian, Nagaraj, Vaishaanth, Miao, Di, Mertens, Mayli, Ting, Daniel Shu Wei, Ong, Jasmine Chiat Ling, Liu, Mingxuan, Cao, Jiuwen, Dunn, Michael, Vaughan, Roger, Ong, Marcus Eng Hock, Sung, Joseph Jao-Yiu, Topol, Eric J, Liu, Nan
The widespread use of ChatGPT and other emerging technology powered by generative artificial intelligence (GenAI) has drawn much attention to potential ethical issues, especially in high-stakes applications such as healthcare, but ethical discussions
Externí odkaz:
http://arxiv.org/abs/2311.02107
Autor:
Liu, Mingxuan, Ning, Yilin, Teixayavong, Salinelat, Mertens, Mayli, Xu, Jie, Ting, Daniel Shu Wei, Cheng, Lionel Tim-Ee, Ong, Jasmine Chiat Ling, Teo, Zhen Ling, Tan, Ting Fang, Narrendar, Ravi Chandran, Wang, Fei, Celi, Leo Anthony, Ong, Marcus Eng Hock, Liu, Nan
Artificial intelligence (AI) has demonstrated the ability to extract insights from data, but the issue of fairness remains a concern in high-stakes fields such as healthcare. Despite extensive discussion and efforts in algorithm development, AI fairn
Externí odkaz:
http://arxiv.org/abs/2304.13493
Autor:
Ning, Yilin, Teixayavong, Salinelat, Shang, Yuqing, Savulescu, Julian, Nagaraj, Vaishaanth, Miao, Di, Mertens, Mayli, Ting, Daniel Shu Wei, Ong, Jasmine Chiat Ling, Liu, Mingxuan, Cao, Jiuwen, Dunn, Michael, Vaughan, Roger, Ong, Marcus Eng Hock, Sung, Joseph Jao-Yiu, Topol, Eric J, Liu, Nan *
Publikováno v:
In The Lancet Digital Health November 2024 6(11):e848-e856
