AIMS: This study aims to develop and validate an optimal model for predicting worsening heart failure (WHF). Multiple machine learning (ML) algorithms were compared, and the results were interpreted using SHapley Additive exPlanations (SHAP). A clini...
BACKGROUND: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast cancer (BC) patients with three or more positive sentinel lymph nodes (SLNs). However, ALND can lead to significant postoperative complications without a...
International journal of cosmetic science
Sep 1, 2024
OBJECTIVE: The objective of this study is to assess the correspondence, in live conditions, between clinical gradings of facial aging signs by three dermatologists and those afforded by an automatic AI-based algorithm that analyses smartphones' selfi...
BACKGROUND: With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical tre...
BACKGROUND: Our study delves into postpartum depression (PPD) extending observation up to six months postpartum, addressing the gap in long-term follow-ups and uncover critical intervention points.
BACKGROUND: Adequate professional preparation of nursing undergraduates is conducive to developing health care careers. Deep learning is important for enhancing nursing competencies and the overall quality of students. However, limited research has b...
BACKGROUND: Evaluating the accuracy and educational utility of artificial intelligence-generated medical cases, especially those produced by large language models such as ChatGPT-4 (developed by OpenAI), is crucial yet underexplored.
OBJECTIVE: Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CTEs) in e...
BACKGROUND: The literature is replete with favorable face-lift results, yet the objective facial rejuvenation outcome measures in Chinese women have remained poorly understood.
BACKGROUND: Machine learning (ML) risk prediction models, although much more accurate than traditional statistical methods, are inconvenient to use in clinical practice due to their nontransparency and requirement of a large number of input variables...
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