This paper seeks to enhance the performance of Mel Frequency Cepstral Coefficients (MFCCs) for detecting abnormal heart sounds. Heart sounds are first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with...
BACKGROUND: Acute myocardial infarction (AMI) remains a leading cause of hospitalization and death in China. Accurate mortality prediction of inpatient is crucial for clinical decision-making of non-ST-segment elevation myocardial infarction (NSTEMI)...
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effective...
The traditional machine learning methods such as decision tree (DT), random forest (RF), and support vector machine (SVM) have low classification performance. This paper proposes an algorithm for the dry bean dataset and obesity levels dataset that c...
HPB : the official journal of the International Hepato Pancreato Biliary Association
Dec 19, 2024
BACKGROUND: Cystic echinococcosis (CE) is a significant public health issue, primarily affecting the liver. While several management strategies exist, there is a lack of predictive tools to guide surgical decisions for hepatic CE. This study aimed to...
BACKGROUND: The use of the modern family planning method provides chances for women to reach optimal child spacing, increase quality of life, increase economic status, achieve the desired family size, and prevent unsafe abortions and maternal and per...
BACKGROUND: To protect patients during anesthesia, difficult airway management is a serious issue that needs to be carefully planned for and carried out. Machine learning prediction tools have recently become increasingly common in medicine, frequent...
Environmental science and pollution research international
Dec 16, 2024
Wastewater treatment plants in Coimbatore South are under pressure from rapid urbanization, inadequate infrastructure, and industrial pollution, leading to environmental and public health concerns. This study aimed to identify suitable locations for ...
OBJECTIVE: This study aimed to develop a prediction tool to identify abdominal aortic aneurysms (AAAs) at increased risk of rupture incorporating demographic, clinical, imaging, and medication data using artificial intelligence (AI).
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