Applied psychology. Health and well-being
Aug 23, 2024
Previous research has demonstrated the influence of commensal dining between humans on food choices, whereas we conducted two studies to examine how the presence of a robot might influence people's choices between meat-heavy and vegetable-forward mea...
Fatigue driving is one of the leading causes of traffic accidents, and the rapid and accurate detection of driver fatigue is of paramount importance for enhancing road safety. However, the application of deep learning models in fatigue driving detect...
OBJECTIVE: To develop machine learning models using patient and migraine features that can predict treatment responses to commonly used migraine preventive medications.
BMC medical informatics and decision making
Aug 23, 2024
Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressu...
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...
Notification systems that convey urgency without adding cognitive burden are crucial in human-computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing ...
High-grade glioma (HGG) is an aggressive brain tumor. Sex is an important factor that differentially affects survival outcomes in HGG. We used an end-to-end deep learning approach on hematoxylin and eosin (H&E) scans to (i) identify sex-specific hist...
IEEE journal of translational engineering in health and medicine
Aug 23, 2024
The integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) can facilitate the advancement of brain-computer interfaces (BCIs). However, existing research in this domain has grappled with the challenge of the eff...
AIM: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults.
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