The recognition of human activity by wearable sensors has garnered significant interest owing to its extensive applications in health, sports, and surveillance systems. This paper presents a novel hybrid deep learning model, termed CNNd-TAm, for the ...
Human activity recognition (HAR) has been one of the active research areas for the past two years for its vast applications in several fields like remote monitoring, gaming, health, security and surveillance, and human-computer interaction. Activity ...
Biomedical imaging has developed as a non-invasive and effective approach for early disease diagnosis and health monitoring. Diabetes mellitus (DM) is a severe metabolic disease with a high global incidence, characterized by the improper secretion of...
The heterogeneity of medical images poses significant challenges to accurate disease diagnosis. To tackle this issue, the impact of such heterogeneity on the causal relationship between image features and diagnostic labels should be incorporated into...
In high-velocity sports, hamstring strain injuries are common causes of missed play and have high rates of reinjury. Evaluating the severity and location of a hamstring strain injury, currently graded by a clinician using a semiqualitative muscle inj...
This study investigates the use of machine learning (ML) algorithms to support faster and more accurate diagnosis of polycystic ovary syndrome (PCOS), with a focus on both predictive performance and clinical applicability. Multiple algorithms were ev...
Keratoconus (KCN) is an uncommon corneal disorder where the central cornea undergoes advanced thinning and causes non-uniform astigmatism. This results in metamorphopsia and potential vision loss if it is left untreated. Early detection of KCN is maj...
The evaluation of social and health policies often necessitates understanding the variations in impacts based on recipients' observed characteristics, underscoring the value of estimating treatment effect heterogeneity. In this study, we leverage pre...
During the real-time recognition of porcine abnormal sounds, the accuracy and stability of the recognition method are crucial to guarantee a good performance. For this purpose, an improved Multiple-Support Vector Data Description (Multi-SVDD) is prop...
BACKGROUND: The anatomical relationship between the maxillary sinus and maxillary molars is critical for planning dental procedures such as tooth extraction, implant placement and periodontal surgery.
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