AIMC Topic: ROC Curve

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Machine learning enhances the performance of short and long-term mortality prediction model in non-ST-segment elevation myocardial infarction.

Scientific reports Jun 18, 2021
Machine learning (ML) has been suggested to improve the performance of prediction models. Nevertheless, research on predicting the risk in patients with acute myocardial infarction (AMI) has been limited and showed inconsistency in the performance of...
Area Under Curve Machine Learning Reproducibility of Results Risk Factors Aged Hospital Mortality ROC Curve Models, Theoretical Non-ST Elevated Myocardial Infarction Middle Aged Risk Assessment Time Factors Humans
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A new deep learning algorithm of 12-lead electrocardiogram for identifying atrial fibrillation during sinus rhythm.

Scientific reports Jun 17, 2021
Atrial fibrillation (AF) is the most prevalent arrhythmia and is associated with increased morbidity and mortality. Its early detection is challenging because of the low detection yield of conventional methods. We aimed to develop a deep learning-bas...
Humans Neural Networks, Computer Artificial Intelligence Algorithms Female Aged Male Middle Aged Atrial Fibrillation Deep Learning Probability ROC Curve Models, Cardiovascular Electrocardiography Sinoatrial Node
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Machine learning models to select potential inhibitors of acetylcholinesterase activity from SistematX: a natural products database.

Molecular diversity Jun 16, 2021
Alzheimer's disease is the most common form of dementia, representing 60-70% of dementia cases. The enzyme acetylcholinesterase (AChE) cleaves the ester bonds in acetylcholine and plays an important role in the termination of acetylcholine activity a...
Databases, Pharmaceutical Molecular Dynamics Simulation Acetylcholinesterase Cholinesterase Inhibitors Cheminformatics Area Under Curve Models, Molecular Workflow Humans Machine Learning Algorithms Molecular Docking Simulation Drug Discovery ROC Curve Biological Products Structure-Activity Relationship
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Application of deep learning in the detection of breast lesions with four different breast densities.

Cancer medicine Jun 16, 2021
OBJECTIVE: This retrospective study evaluated the model from populations with different breast densities and showed the model's performance on malignancy prediction.
Calcinosis Mammography Breast Density Middle Aged Deep Learning ROC Curve Triple Negative Breast Neoplasms Humans Retrospective Studies Female Aged Adult Sensitivity and Specificity Breast Neoplasms
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Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer.

Cancer research and treatment Jun 15, 2021
PURPOSE: Machine learning (ML) is a strong candidate for making accurate predictions, as we can use large amount of data with powerful computational algorithms. We developed a ML based model to predict survival of patients with colorectal cancer (CRC...
Colorectal Neoplasms ROC Curve Predictive Value of Tests Humans Machine Learning Survival Rate
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Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Nature biomedical engineering Jun 15, 2021
Regular screening for the early detection of common chronic diseases might benefit from the use of deep-learning approaches, particularly in resource-poor or remote settings. Here we show that deep-learning models can be used to identify chronic kidn...
Humans Middle Aged Disease Progression Deep Learning Blood Glucose Neural Networks, Computer Prospective Studies Female Male Retina Body Height Body Mass Index Image Interpretation, Computer-Assisted Photography Area Under Curve ROC Curve Metadata Fundus Oculi Diabetes Mellitus, Type 2 Body Weight Renal Insufficiency, Chronic Glomerular Filtration Rate
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Improving the Performance of Machine Learning-Based Network Intrusion Detection Systems on the UNSW-NB15 Dataset.

Computational intelligence and neuroscience Jun 15, 2021
Networks are exposed to an increasing number of cyberattacks due to their vulnerabilities. So, cybersecurity strives to make networks as safe as possible, by introducing defense systems to detect any suspicious activities. However, firewalls and clas...
Computer Security Machine Learning ROC Curve Supervised Machine Learning
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Prediction of absenteeism in public schools teachers with machine learning.

Revista de saude publica Jun 14, 2021
OBJECTIVE: To predict the risk of absence from work due to morbidities of teachers working in early childhood education in the municipal public schools, using machine learning algorithms.
Brazil Absenteeism Humans Child, Preschool Machine Learning ROC Curve Schools Cross-Sectional Studies
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A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow-up in patients with acute coronary syndrome.

PloS one Jun 11, 2021
OBJECTIVE: Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine lear...
Middle Aged ROC Curve Follow-Up Studies Non-ST Elevated Myocardial Infarction Republic of Korea Area Under Curve Female Humans ST Elevation Myocardial Infarction Aged Machine Learning Acute Coronary Syndrome Male Algorithms
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Deep-learning based classification distinguishes sarcomatoid malignant mesotheliomas from benign spindle cell mesothelial proliferations.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Jun 10, 2021
Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning...
Neural Networks, Computer Prognosis Sensitivity and Specificity Deep Learning Area Under Curve Humans ROC Curve Mesothelioma Image Processing, Computer-Assisted Mesothelioma, Malignant Cell Proliferation Pleural Neoplasms Diagnosis, Differential
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