AIMC Topic: ROC Curve

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Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.

BMC cancer Dec 25, 2024
BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) exhibits a propensity for early recurrence following liver resection, resulting in a bleak prognosis. At present, majority of the predictive models for the early postoperative recurrence of HCC rely...
Hepatectomy Proportional Hazards Models Liver Neoplasms Humans Carcinoma, Hepatocellular Machine Learning Neoplasm Recurrence, Local Algorithms Prognosis Adult Retrospective Studies Male Female Middle Aged Risk Factors ROC Curve Aged
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A feature fusion method based on radiomic features and revised deep features for improving tumor prediction in ultrasound images.

Computers in biology and medicine Dec 24, 2024
BACKGROUND: Radiomic features and deep features are both vitally helpful for the accurate prediction of tumor information in breast ultrasound. However, whether integrating radiomic features and deep features can improve the prediction performance of...
Female Breast Neoplasms Radiomics Deep Learning Ultrasonography ROC Curve Ultrasonography, Mammary Image Interpretation, Computer-Assisted Humans Neural Networks, Computer
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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis.

EBioMedicine Dec 24, 2024
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study ai...
Precursor Cell Lymphoblastic Leukemia-Lymphoma Leukemia Computer Simulation Humans Leukemia, Myeloid, Acute Machine Learning Diagnosis, Computer-Assisted Algorithms ROC Curve
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Pulmonologists-level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach.

Scientific reports Dec 24, 2024
Lung cancer (LC) remains the primary cause of cancer-related mortality, largely due to late-stage diagnoses. Effective strategies for early detection are therefore of paramount importance. In recent years, machine learning (ML) has demonstrated consi...
Pulmonologists Humans Machine Learning Early Detection of Cancer Retrospective Studies Denmark Middle Aged Female Smoking ROC Curve Hematologic Tests Aged Lung Neoplasms Male
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Understanding Parkinson's: The microbiome and machine learning approach.

Maturitas Dec 23, 2024
OBJECTIVE: Given that Parkinson's disease is a progressive disorder, with symptoms that worsen over time, our goal is to enhance the diagnosis of Parkinson's disease by utilizing machine learning techniques and microbiome analysis. The primary object...
Gastrointestinal Microbiome Parkinson Disease Microbiota Humans Machine Learning Algorithms Female Biomarkers Male Feces ROC Curve
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Anatomy-centred deep learning improves generalisability and progression prediction in radiographic sacroiliitis detection.

RMD open Dec 23, 2024
PURPOSE: To examine whether incorporating anatomy-centred deep learning can improve generalisability and enable prediction of disease progression.
Area Under Curve Radiography Sacroiliac Joint Sacroiliitis Disease Progression Deep Learning ROC Curve Humans Retrospective Studies Female Adult Sensitivity and Specificity Male Middle Aged
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Comparison and analysis of deep learning models for discriminating longitudinal and oblique vaginal septa based on ultrasound imaging.

BMC medical imaging Dec 23, 2024
BACKGROUND: The longitudinal vaginal septum and oblique vaginal septum are female müllerian duct anomalies that are relatively less diagnosed but severely fertility-threatening in clinical practice. Ultrasound imaging is commonly used to examine the ...
Sensitivity and Specificity Deep Learning Ultrasonography ROC Curve Humans Neural Networks, Computer Female Adult Diagnosis, Differential Vagina Urogenital Abnormalities
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Machine Learning to Predict the Individual Risk of Treatment-Relevant Toxicity for Patients With Breast Cancer Undergoing Neoadjuvant Systemic Treatment.

JCO clinical cancer informatics Dec 23, 2024
PURPOSE: Toxicity to systemic cancer treatment represents a major anxiety for patients and a challenge to treatment plans. We aimed to develop machine learning algorithms for the upfront prediction of an individual's risk of experiencing treatment-re...
Drug-Related Side Effects and Adverse Reactions Female Aged Adult Humans Middle Aged Breast Neoplasms Machine Learning ROC Curve Algorithms Neoadjuvant Therapy Prognosis Support Vector Machine
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Area under the ROC Curve has the most consistent evaluation for binary classification.

PloS one Dec 23, 2024
The proper use of model evaluation metrics is important for model evaluation and model selection in binary classification tasks. This study investigates how consistent different metrics are at evaluating models across data of different prevalence whi...
Machine Learning Area Under Curve ROC Curve Sample Size Models, Statistical Data Interpretation, Statistical Evaluation Studies as Topic
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Neural networks for predicting etiological diagnosis of uveitis.

Eye (London, England) Dec 20, 2024
BACKGROUND/OBJECTIVES: The large number and heterogeneity of causes of uveitis make the etiological diagnosis a complex task. The clinician must consider all the information concerning the ophthalmological and extra-ophthalmological features of the p...
Algorithms Retrospective Studies Female Humans Middle Aged Aged Neural Networks, Computer Adolescent Machine Learning Young Adult ROC Curve Adult Uveitis Sensitivity and Specificity Male
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