Heart attack detection and treatment in women remain significantly under-optimized due to differences in symptom presentation and physiological characteristics compared to men, leading to delayed or incorrect diagnoses. Addressing this gap, this stud...
As technological innovation in computers has advanced, radiologists may now diagnose brain tumors (BT) with the use of artificial intelligence (AI). In the medical field, early disease identification enables further therapies, where the use of AI sys...
BACKGROUND: Accurate tracking and enumeration of surgical instruments are critical for patient safety and operational efficiency in laparoscopic procedures. Advanced tracking systems enhance object detection by maintaining instrument identity despite...
BACKGROUND: Evidence-based medicine combines scientific research, clinical expertise, and patient preferences to enhance the patient outcomes and improve health care quality. Clinical data are crucial in aligning medical decisions with evidence-based...
Due to large intra-subject and inter-subject variabilities of electroencephalogram (EEG) signals, EEG-based brain-computer interfaces (BCIs) usually need subject-specific calibration to tailor the decoding algorithm for each new subject, which is tim...
E-commerce is a vital component of the world economy, providing people with a simple and convenient method for shopping and enabling businesses to expand into new global markets. Improving e-commerce decision-making by utilizing IoT and machine intel...
Predicting student performance is crucial for providing personalized support and enhancing academic performance. Advanced machine-learning approaches are being used to understand student performance variables as educational data grows. A big dataset ...
BACKGROUND: The basal septal hypertrophy(BSH) is an often under-recognized morphological change in the left ventricle. This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functi...
BACKGROUND: Rare diseases often present with a variety of clinical symptoms and therefore are challenging to diagnose. Fabry disease is an x-linked rare metabolic disorder. The severity of symptoms is usually different in men and women. Since therape...
Random Forest (RF) is a powerful ensemble-based supervised machine learning technique that builds multiple decision trees using bootstrap aggregating and random feature selection to improve classification and regression accuracy while reducing overfi...
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