BACKGROUND: This study aims to utilize the deep learning method of VB-Net to locate and segment the trigeminal nerve, and employ radiomics methods to distinguish between CTN patients and healthy individuals.
BACKGROUND: Integrating Artificial Intelligence (AI) in educational applications is becoming increasingly prevalent, bringing opportunities and challenges to the learning environment. While AI applications have the potential to enhance structured lea...
OBJECTIVE: Colorectal cancer (CRC) is the fourth most common cancer in the UK. Patients with symptoms suggestive of CRC should be referred for urgent investigation. However, gastrointestinal symptoms are often non-specific and there is a need for sui...
BACKGROUND: Cognitive impairment and dementia pose a significant challenge to the aging population, impacting the well-being, quality of life, and autonomy of affected individuals. As the population ages, this will place enormous strain on health car...
Journal of cancer research and clinical oncology
Sep 16, 2024
BACKGROUND: This study aims to establish a predictive model for assessing the risk of esophageal cancer lung metastasis using machine learning techniques.
OBJECTIVES: This study aimed to assess the accuracy of machine learning (ML) models with feature selection technique in classifying cervical vertebral maturation stages (CVMS). Consensus-based datasets were used for models training and evaluation for...
We investigated fluctuations of the photoplethysmography (PPG) waveform in patients undergoing surgery. There is an association between the morphologic variation extracted from arterial blood pressure (ABP) signals and short-term surgical outcomes. T...
Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molecular understanding of MI is elusive and needs to be fully explored. This study aimed to elucidate th...
Expert review of endocrinology & metabolism
Sep 16, 2024
BACKGROUND: The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast the risk of hypoglycemia among ICU patients in Jordan.
PURPOSE: There is limited understanding of the link between exposure to heavy metals and ischemic stroke (IS). This research aimed to develop efficient and interpretable machine learning (ML) models to associate the relationship between exposure to h...
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