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Nurse-Delivered Telehealth in Home-Based Palliative Care: Integrative Systematic Review

Nurse-Delivered Telehealth in Home-Based Palliative Care: Integrative Systematic Review

We developed a detailed search strategy informed by previous literature [8,13,26,27] and refined by a research librarian (Y Zhang) (Multimedia Appendix 2). There are three main parts in the search strategy: (1) terms related to “palliative care,” including the clinical content of palliative care, such as symptom management, spiritual support, grief support, etc; (2) terms related to “telehealth”; and (3) terms related to “nursing.”

Cong Ma, Yifan Fang, Hui Zhang, Ying Zheng, Ying Zhang, Wanchen Zhao, Ge Yan, Yaoxin Zeng, Yanwu Zhang, Xiaohong Ning, Zhimeng Jia, Na Guo

J Med Internet Res 2025;27:e73024

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Clinical Laboratory Parameter–Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study

Jin et al [17] reported that a result from a user study using large language model framework, Trial GPT, to support patient matching resulted in a 42.6% decrease in the screening time [18]. Another AI approach is clinical trial digital twin technology [18-21]. Digital twin technology creates virtual patients that replicate individual characteristics, enabling the prediction of clinical responses [18,19,21]. By utilizing digital twins, the required sample sizes for clinical trials can be reduced [18,19,21].

Byungeun Shon, Sook Jin Seong, Eun Jung Choi, Mi-Ri Gwon, Hae Won Lee, Jaechan Park, Ho-Young Chung, Sungmoon Jeong, Young-Ran Yoon

JMIR AI 2025;4:e64845