AIMC Topic: 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...
ROC Curve Female Lymphadenopathy Aged Abdomen Adult Lymph Nodes Male Humans Middle Aged Neural Networks, Computer Artificial Intelligence 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...
Male Female Neoplasm Staging Middle Aged Humans Aged Neoplasm Grading Deep Learning Adult Adenocarcinoma of Lung Algorithms ROC Curve Radiomics Prognosis Lung Neoplasms Retrospective Studies Tomography, X-Ray Computed
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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 ...
Rectal Neoplasms Image Interpretation, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Neoadjuvant Therapy Magnetic Resonance Imaging Neoplasm Staging Adult Radiomics Algorithms Male Prognosis Middle Aged Retrospective Studies Female Aged Humans Machine Learning
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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 Image Processing, Computer-Assisted Retrospective Studies Radiomics Support Vector Machine Tomography, X-Ray Computed Uterine Cervical Neoplasms Female Middle Aged Aged ROC Curve Adult
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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 Diagnosis, Differential Tomography, Spiral Computed Female Aged Adult Sensitivity and Specificity Male Middle Aged Deep Learning ROC Curve Lung Neoplasms Multiple Pulmonary Nodules Humans Algorithms Retrospective Studies
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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 ...
Child, Preschool Child ROC Curve Logistic Models Support Vector Machine Tonsillectomy Emergence Delirium Adenoidectomy Machine Learning Female Male Risk Assessment Adolescent Humans
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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.
Radiomics Male Infant Adolescent Child, Preschool Algorithms Retrospective Studies Tomography, X-Ray Computed Female Bone Marrow Neoplasms Neuroblastoma Child ROC Curve Support Vector Machine Contrast Media Bone Marrow Humans Machine Learning
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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.
Humans Machine Learning Prognosis Magnetic Resonance Imaging Breast Neoplasms Area Under Curve Radiomics Image Interpretation, Computer-Assisted Biomarkers, Tumor Retrospective Studies Carcinoma, Ductal, Breast Middle Aged Female Ki-67 Antigen ROC Curve Aged Adult
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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...
Gene Expression Regulation, Neoplastic Support Vector Machine Ferroptosis Metaplasia Transcriptome ROC Curve Protein Interaction Maps Computational Biology Humans Machine Learning Stomach Neoplasms Biomarkers, Tumor Gene Expression Profiling
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Machine learning model for osteoporosis diagnosis based on bone turnover markers.

Health informatics journal Jan 1, 2024
To assess the diagnostic utility of bone turnover markers (BTMs) and demographic variables for identifying individuals with osteoporosis. A cross-sectional study involving 280 participants was conducted. Serum BTM values were obtained from 88 patient...
Humans Cross-Sectional Studies Male Middle Aged ROC Curve Bone Remodeling Machine Learning Biomarkers Osteoporosis Female Aged
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