AIMC Topic: ROC Curve
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Exploring Ovarian Cancer Prediction Models and Potential Markers Using Machine Learning.
Annals of clinical and laboratory science
Mar 1, 2025
OBJECTIVE: To develop machine learning models, facilitate a more accurate diagnosis of ovarian cancer (OC), and explore potential markers.
Application of Interpretable Machine Learning Models to Predict the Risk Factors of HBV-Related Liver Cirrhosis in CHB Patients Based on Routine Clinical Data: A Retrospective Cohort Study.
Journal of medical virology
Mar 1, 2025
Chronic hepatitis B (CHB) infection represents a significant global public health issue, often leading to hepatitis B virus (HBV)-related liver cirrhosis (HBV-LC) with poor prognoses. Early identification of HBV-LC risk is essential for timely interv...
Identification and Validation of Four Serum Biomarkers With Optimal Diagnostic and Prognostic Potential for Gastric Cancer Based on Machine Learning Algorithms.
Cancer medicine
Mar 1, 2025
BACKGROUND: Gastric cancer (GC) is considered a highly heterogeneous disease, and currently, a comprehensive approach encompassing molecular data from various biological levels is lacking.
Predicting Neoplastic Polyp in Patients With Gallbladder Polyps Using Interpretable Machine Learning Models: Retrospective Cohort Study.
Cancer medicine
Mar 1, 2025
OBJECTIVE: Gallbladder polyps (GBPs) are increasingly prevalent, with the majority being benign; however, neoplastic polyps carry a risk of malignant transformation, highlighting the importance of accurate differentiation. This study aimed to develop...
Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Mar 1, 2025
INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of which can only be determined post mortem. Here, we developed machine learning models, the Florey CAA Score (FCAAS), to predict CAA severity (none/mild/mod...
Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery.
Yonsei medical journal
Mar 1, 2025
PURPOSE: To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.
MRI-Based Topology Deep Learning Model for Noninvasive Prediction of Microvascular Invasion and Assisting Prognostic Stratification in HCC.
Liver international : official journal of the International Association for the Study of the Liver
Mar 1, 2025
BACKGROUND & AIMS: Microvascular invasion (MVI) is associated with poor prognosis in hepatocellular carcinoma (HCC). Topology may improve the predictive performance and interpretability of deep learning (DL). We aimed to develop and externally valida...
CATALYZE: a deep learning approach for cataract assessment and grading on SS-OCT images.
Journal of cataract and refractive surgery
Mar 1, 2025
PURPOSE: To assess a new objective deep learning model cataract grading method based on swept-source optical coherence tomography (SS-OCT) scans provided by the Anterion.
Machine learning model-based prediction of postpancreatectomy acute pancreatitis following pancreaticoduodenectomy: A retrospective cohort study.
World journal of gastroenterology
Feb 28, 2025
BACKGROUND: The International Study Group of Pancreatic Surgery has established the definition and grading system for postpancreatectomy acute pancreatitis (PPAP). There are no established machine learning models for predicting PPAP following pancrea...
Deep learning model for identifying acute heart failure patients using electrocardiography in the emergency room.
European heart journal. Acute cardiovascular care
Feb 20, 2025
AIMS: Acute heart failure (AHF) poses significant diagnostic challenges in the emergency room (ER) because of its varied clinical presentation and limitations of traditional diagnostic methods. This study aimed to develop and evaluate a deep learning...
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