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http://dx.doi.org/10.1590/S2237-96222024V33E20231407.EN | DOI Listing |
J Med Internet Res
January 2025
Department of Nephrology, Hunan Key Laboratory of Kidney Disease and Blood Purification, The Second Xiangya Hospital of Central South University, Changsha, China.
Background: Acute kidney injury (AKI) is a common complication in hospitalized older patients, associated with increased morbidity, mortality, and health care costs. Major adverse kidney events within 30 days (MAKE30), a composite of death, new renal replacement therapy, or persistent renal dysfunction, has been recommended as a patient-centered endpoint for clinical trials involving AKI.
Objective: This study aimed to develop and validate a machine learning-based model to predict MAKE30 in hospitalized older patients with AKI.
JMIR Med Inform
January 2025
Sungkyunkwan University, Seoul, Republic of Korea.
Background: Mental health chatbots have emerged as a promising tool for providing accessible and convenient support to individuals in need. Building on our previous research on digital interventions for loneliness and depression among Korean college students, this study addresses the limitations identified and explores more advanced artificial intelligence-driven solutions.
Objective: This study aimed to develop and evaluate the performance of HoMemeTown Dr.
JMIR Res Protoc
January 2025
Department of Women's and Children's Health, Participatory eHealth and Health Data Research Group, Uppsala University, Uppsala, Sweden.
Background: Digital health interventions have become increasingly popular in recent years, expanding the possibilities for treatment for various patient groups. In clinical research, while the design of the intervention receives close attention, challenges with research participant engagement and retention persist. This may be partially due to the use of digital health platforms, which may lack adequacy for participants.
View Article and Find Full Text PDFJ Neurosurg Spine
January 2025
6Presbyterian St. Lukes Medical Center, Denver, Colorado.
Objective: Malalignment following cervical spine deformity (CSD) surgery can negatively impact outcomes and increase complications. Despite the growing ability to plan alignment, it remains unclear whether preoperative goals are achieved with surgery. The objective of this study was to assess how good surgeons are at achieving their preoperative goal alignment following CSD surgery.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!