Supporting Trustworthy AI Through Machine Unlearning.
Machine unlearning can enhance trustworthy AI by supporting ethical principles. However, it poses ethical risks that need addressing. 🤖📜
Fall risk prediction using temporal gait features and machine learning approaches.
AI enhances fall risk prediction through gait analysis. 🤖🚶♂️ Promising results with 96% accuracy using machine learning techniques. 📊
Adult co-creators’ emotional and psychological experiences of the co-creation process: a Health CASCADE scoping review protocol.
Exploring adult co-creators' emotional and psychological experiences in health co-creation processes. 🧠🤝 #HealthCASCADE #CoCreation
Comparing Cadence vs. Machine Learning Based Physical Activity Intensity Classifications: Variations in the Associations of Physical Activity With Mortality.
New research compares cadence and machine learning in classifying physical activity intensity and its impact on mortality. 📊🏃♂️
Treatment effect analysis of the Frailty Care Bundle (FCB) in a cohort of patients in acute care settings.
Exploring the Frailty Care Bundle's impact on older patients' mobility using machine learning. 🤖👵 #Healthcare #FrailtyCare
Analysis of Responses of GPT-4 V to the Japanese National Clinical Engineer Licensing Examination.
GPT-4 V scored 86% on Japan's Clinical Engineer Exam. 📊 Performance varied by subject; caution advised in usage. ⚠️
Multispectral imaging in medicine: A bibliometric study.
Multispectral imaging shows promise in medicine. 📊 Our review of a recent study highlights its potential and future applications. 🩺✨
Using machine learning to predict bacteremia in urgent care patients on the basis of triage data and laboratory results.
Machine learning models show promise in predicting bacteremia in urgent care patients. 📊🤖 Early detection can save lives! 🏥