AIMC Topic: ROC Curve

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Assessing performance of artificial neural networks and re-sampling techniques for healthcare datasets.

Health informatics journal Jan 1, 2022
Re-sampling methods to solve class imbalance problems have shown to improve classification accuracy by mitigating the bias introduced by differences in class size. However, it is possible that a model which uses a specific re-sampling technique prior...
ROC Curve Humans Health Facilities Neural Networks, Computer Data Collection Delivery of Health Care
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Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.

Journal of X-ray science and technology Jan 1, 2022
BACKGROUND: Lung cancer is one of the most common cancers, and early diagnosis and intervention can improve cancer cure rate.
Support Vector Machine Lung ROC Curve Lung Neoplasms Biomarkers Retrospective Studies Humans Machine Learning
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Diagnostic Performance of AI for Cancers Registered in A Mammography Screening Program: A Retrospective Analysis.

Technology in cancer research & treatment Jan 1, 2022
To evaluate the performance of an artificial intelligence (AI) algorithm in a simulated screening setting and its effectiveness in detecting missed and interval cancers. Digital mammograms were collected from Bahcesehir Mammographic Screening Progr...
Population Surveillance Mammography Turkey Image Processing, Computer-Assisted Mass Screening Early Detection of Cancer Retrospective Studies Female Risk Factors Breast Neoplasms Risk Assessment ROC Curve Humans Artificial Intelligence
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Detection and Weak Segmentation of Masses in Gray-Scale Breast Mammogram Images Using Deep Learning.

Yonsei medical journal Jan 1, 2022
PURPOSE: In this paper, we propose deep-learning methodology with which to enhance the mass differentiation performance of convolutional neural network (CNN)-based architecture.
Breast Neoplasms Deep Learning ROC Curve Humans Neural Networks, Computer Female Mammography Cell Differentiation
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Developing an Image-Based Deep Learning Framework for Automatic Scoring of the Pentagon Drawing Test.

Journal of Alzheimer's disease : JAD Jan 1, 2022
BACKGROUND: The Pentagon Drawing Test (PDT) is a common assessment for visuospatial function. Evaluating the PDT by artificial intelligence can improve efficiency and reliability in the big data era. This study aimed to develop a deep learning (DL) f...
Neural Networks, Computer Deep Learning Humans Mental Status and Dementia Tests Retrospective Studies ROC Curve Cognition Reproducibility of Results
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EVALUATION OF ARTIFICIAL INTELLIGENCE-BASED QUANTITATIVE ANALYSIS TO IDENTIFY CLINICALLY SIGNIFICANT SEVERE RETINOPATHY OF PREMATURITY.

Retina (Philadelphia, Pa.) Jan 1, 2022
PURPOSE: To evaluate the screening potential of a deep learning algorithm-derived severity score by determining its ability to detect clinically significant severe retinopathy of prematurity (ROP).
Infant, Newborn Male Severity of Illness Index Algorithms Humans Retrospective Studies Artificial Intelligence Female Deep Learning Retina ROC Curve Gestational Age Follow-Up Studies Ophthalmoscopy Retinopathy of Prematurity
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[Development and evaluation of a machine learning prediction model for large for gestational age].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi Dec 10, 2021
To develop and validate a useful predictive model for large gestational age (LGA) in pregnancy using a machine learning (ML) algorithm and compare its performance with the traditional logistic regression model. Data were obtained from the National ...
Infant, Newborn Male Infant Algorithms ROC Curve Humans Pregnancy Logistic Models Machine Learning Female Gestational Age
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Effective End-to-End Deep Learning Process in Medical Imaging Using Independent Task Learning: Application for Diagnosis of Maxillary Sinusitis.

Yonsei medical journal Dec 1, 2021
PURPOSE: This study aimed to propose an effective end-to-end process in medical imaging using an independent task learning (ITL) algorithm and to evaluate its performance in maxillary sinusitis applications.
Humans Retrospective Studies Deep Learning ROC Curve Radiography Maxillary Sinusitis
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Automated Assessment of Brain CT After Cardiac Arrest-An Observational Derivation/Validation Cohort Study.

Critical care medicine Dec 1, 2021
OBJECTIVES: Prognostication of outcome is an essential step in defining therapeutic goals after cardiac arrest. Gray-white-matter ratio obtained from brain CT can predict poor outcome. However, manual placement of regions of interest is a potential s...
Tomography, X-Ray Computed Female Humans Male ROC Curve Aged Machine Learning Validation Studies as Topic Heart Arrest Brain Middle Aged Cohort Studies
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Prediction of RBP binding sites on circRNAs using an LSTM-based deep sequence learning architecture.

Briefings in bioinformatics Nov 5, 2021
Circular RNAs (circRNAs) are widely expressed in highly diverged eukaryotes. Although circRNAs have been known for many years, their function remains unclear. Interaction with RNA-binding protein (RBP) to influence post-transcriptional regulation is ...
Databases, Genetic ROC Curve Base Sequence Algorithms RNA, Circular Reproducibility of Results Computational Biology Binding Sites Deep Learning RNA-Binding Proteins
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