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Interpretable machine learning models for prolonged Emergency Department wait time prediction.
BMC health services research
Mar 18, 2025
OBJECTIVE: Prolonged Emergency Department (ED) wait times lead to diminished healthcare quality. Utilizing machine learning (ML) to predict patient wait times could aid in ED operational management. Our aim is to perform a comprehensive analysis of M...
A semi-supervised convolutional neural network for diagnosis of pancreatic ductal adenocarcinoma based on EUS-FNA cytological images.
BMC cancer
Mar 18, 2025
BACKGROUND: The cytological diagnostic process of EUS-FNA smears is time-consuming and manpower-intensive, and the conclusion could be subjective and controversial. Moreover, the relative lack of cytopathologists has limited the widespread implementa...
Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI).
BMC psychiatry
Mar 18, 2025
BACKGROUND: Accurately diagnosing Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) shows significant challenges as traditional diagnostic methods fail to meet expectations due to patient hesitance and non-psychiatric h...
Deep learning based on intratumoral heterogeneity predicts histopathologic grade of hepatocellular carcinoma.
BMC cancer
Mar 18, 2025
OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (ITH) is increasingly being recognized. This study aimed to investigate the value of the ITH-based deep learning model for preoperative prediction of his...
Leveraging machine learning for precision medicine: a predictive model for cognitive impairment in cholestasis patients.
BMC gastroenterology
Mar 18, 2025
BACKGROUND: Cholestasis, characterized by impaired bile flow, impacts cognitive function through systemic mechanisms, including inflammation and metabolic dysregulation. Despite its significance, targeted predictive models for cognitive impairment in...
Life's Crucial 9 and NAFLD from association to SHAP-interpreted machine learning predictions.
Scientific reports
Mar 18, 2025
Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. Cardiovascular disease (CVD) and NAFLD share multiple common risk factors. Life's Crucial 9 (LC9), a novel indicator for comprehensive assessment of card...
Construction of a machine learning-based interpretable prediction model for acute kidney injury in hospitalized patients.
Scientific reports
Mar 18, 2025
In this observational study, we used data from 59,936 hospitalized adults to construct a model. For the models constructed with all 53 variables, all five models achieved acceptable performance with the validation cohort, with the extreme gradient bo...
Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.
Scientific reports
Mar 18, 2025
Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving the common practice of screening for Mild Cognitive Impairment (MCI). However, the progressive nature of AD makes it challenging to identify its causa...
Machine learning predicts spinal cord stimulation surgery outcomes and reveals novel neural markers for chronic pain.
Scientific reports
Mar 18, 2025
Spinal cord stimulation (SCS) is a well-accepted therapy for refractory chronic pain. However, predicting responders remain a challenge due to a lack of objective pain biomarkers. The present study applies machine learning to predict which patients w...
Identifying novel risk factors for aneurysmal subarachnoid haemorrhage using machine learning.
Scientific reports
Mar 18, 2025
Aneurysmal subarachnoid haemorrhage (aSAH) is a type of stroke with high mortality and morbidity. This study aimed to identify novel aSAH risk factors by combining machine learning (ML) and traditional statistical methods. Using the UK Biobank, we id...
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