AIMC Topic: ROC Curve

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Integrative approach for predicting drug-target interactions via matrix factorization and broad learning systems.

Mathematical biosciences and engineering : MBE Jan 18, 2024
In the drug discovery process, time and costs are the most typical problems resulting from the experimental screening of drug-target interactions (DTIs). To address these limitations, many computational methods have been developed to achieve more acc...
Neural Networks, Computer Drug Discovery ROC Curve
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The Added Effect of Artificial Intelligence in CT Assessment of Abdominal Lymphadenopathy.

Lymphology Jan 1, 2024
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy contr...
Female Middle Aged Lymph Nodes Humans ROC Curve Aged Neural Networks, Computer Lymphadenopathy Adult Artificial Intelligence Abdomen Male Tomography, X-Ray Computed
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Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.

Technology in cancer research & treatment Jan 1, 2024
INTRODUCTION: This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patien...
Radiomics Male Middle Aged Deep Learning ROC Curve Tomography, X-Ray Computed Lung Neoplasms Humans Female Neoplasm Staging Aged Algorithms Neoplasm Grading Adult Prognosis Adenocarcinoma of Lung Retrospective Studies
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Prediction of T Stage of Rectal Cancer After Neoadjuvant Therapy by Multi-Parameter Magnetic Resonance Radiomics Based on Machine Learning Algorithms.

Technology in cancer research & treatment Jan 1, 2024
INTRODUCTION: Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop accurate methods to predict the post-treatment T (pT) stage. The purpose of this study was to evaluate ...
Magnetic Resonance Imaging Neoplasm Staging Rectal Neoplasms Image Interpretation, Computer-Assisted Male Middle Aged ROC Curve Image Processing, Computer-Assisted Neoadjuvant Therapy Female Humans Aged Machine Learning Adult Algorithms Radiomics Prognosis Retrospective Studies
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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

Technology in cancer research & treatment Jan 1, 2024
This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervic...
Humans Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Uterine Cervical Neoplasms Middle Aged ROC Curve Image Processing, Computer-Assisted Female Support Vector Machine Aged Adult Radiomics
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The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules ha...
Solitary Pulmonary Nodule Humans Diagnosis, Differential Deep Learning Tomography, Spiral Computed Aged Algorithms ROC Curve Adult Retrospective Studies Lung Neoplasms Sensitivity and Specificity Female Multiple Pulmonary Nodules Male Middle Aged
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Data-driven Machine Learning Models for Risk Stratification and Prediction of Emergence Delirium in Pediatric Patients Underwent Tonsillectomy/Adenotonsillectomy.

Annali italiani di chirurgia Jan 1, 2024
AIM: In the pediatric surgical population, Emergence Delirium (ED) poses a significant challenge. This study aims to develop and validate machine learning (ML) models to identify key features associated with ED and predict its occurrence in children ...
Tonsillectomy Emergence Delirium Adenoidectomy Female Male Risk Assessment Adolescent Child, Preschool Child ROC Curve Logistic Models Support Vector Machine Humans Machine Learning
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Predicting Bone Marrow Metastasis in Neuroblastoma: An Explainable Machine Learning Approach Using Contrast-Enhanced Computed Tomography Radiomics Features.

Technology in cancer research & treatment Jan 1, 2024
PURPOSE: To predict bone marrow metastasis in neuroblastoma using contrast-enhanced computed tomography (CECT) radiomics features and explainable machine learning.
Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Humans Child, Preschool Child ROC Curve Support Vector Machine Contrast Media Radiomics Male Infant Adolescent Bone Marrow Bone Marrow Neoplasms Neuroblastoma
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Radiomic Machine Learning in Invasive Ductal Breast Cancer: Prediction of Ki-67 Expression Level Based on Radiomics of DCE-MRI.

Technology in cancer research & treatment Jan 1, 2024
PURPOSE: Our study aimed to investigate the potential of radiomics with DCE-MRI for predicting Ki-67 expression in invasive ductal breast cancer.
Carcinoma, Ductal, Breast Ki-67 Antigen Adult Middle Aged Machine Learning Breast Neoplasms Humans ROC Curve Prognosis Radiomics Magnetic Resonance Imaging Retrospective Studies Biomarkers, Tumor Area Under Curve Female Image Interpretation, Computer-Assisted Aged
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Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

Technology in cancer research & treatment Jan 1, 2024
BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this stud...
Stomach Neoplasms Biomarkers, Tumor Gene Expression Profiling Transcriptome ROC Curve Humans Machine Learning Ferroptosis Metaplasia Protein Interaction Maps Computational Biology Gene Expression Regulation, Neoplastic Support Vector Machine
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