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Using Machine Learning to Improve Readmission Risk in Surgical Patients in South Africa.
International journal of environmental research and public health
Feb 26, 2025
Unplanned readmission within 30 days is a major challenge both globally and in South Africa. The aim of this study was to develop a machine learning model to predict unplanned surgical and trauma readmission to a public hospital in South Africa from ...
Untargeted Lipidomic Biomarkers for Liver Cancer Diagnosis: A Tree-Based Machine Learning Model Enhanced by Explainable Artificial Intelligence.
Medicina (Kaunas, Lithuania)
Feb 26, 2025
: Liver cancer ranks among the leading causes of cancer-related mortality, necessitating the development of novel diagnostic methods. Deregulated lipid metabolism, a hallmark of hepatocarcinogenesis, offers compelling prospects for biomarker identifi...
Imbalanced Power Spectral Generation for Respiratory Rate and Uncertainty Estimations Based on Photoplethysmography Signal.
Sensors (Basel, Switzerland)
Feb 26, 2025
Respiratory rate (RR) changes in the elderly can indicate serious diseases. Thus, accurate estimation of RRs for cardiopulmonary function is essential for home health monitoring systems. However, machine learning (ML) algorithm errors embedded in hea...
CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.
BMC geriatrics
Feb 26, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...
Using deep learning to differentiate among histology renal tumor types in computed tomography scans.
BMC medical imaging
Feb 26, 2025
BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography (CT) scans with the aim of differentiating among renal tumors according to histologic sub-type.
Utilization of tree-based machine learning models for predicting low birth weight cases.
BMC pregnancy and childbirth
Feb 26, 2025
BACKGROUND: Low birth weight (LBW) is a health condition that affects over 20 million gestational outcomes worldwide. The current literature indicates that machine learning models have the potential to assist healthcare professionals in predicting LB...
Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.
Scientific reports
Feb 26, 2025
Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to being able to mimic different rheumatological, neurological and dermatological diseases, leprosy is underdiagnosed because several professionals present ...
Combining an improved political optimizer with convolutional neural networks for accurate anterior cruciate ligament tear detection in sports injuries.
Scientific reports
Feb 26, 2025
A new technique has been developed to identify ACL tears in sports injuries. This method utilizes a Convolutional Neural Network (CNN) in combination with a modified Political Optimizer (IPO) algorithm, resulting in a major breakthrough in detecting ...
Early detection of feline chronic kidney disease via 3-hydroxykynurenine and machine learning.
Scientific reports
Feb 26, 2025
Feline chronic kidney disease (CKD) is one of the most frequently encountered diseases in veterinary practice, and the leading cause of mortality in cats over five years of age. While diagnosing advanced CKD is straightforward, current routine tests ...
Predicting the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis using a stacked ensemble machine learning model: a retrospective study based on the MIMIC database.
BMJ open
Feb 26, 2025
OBJECTIVE: This study developed and validated a stacked ensemble machine learning model to predict the risk of acute kidney injury in patients with acute pancreatitis complicated by sepsis.
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