AIMC Topic: Predictive Value of Tests

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Fuzzy partitioning of clinical data for DMT2 patients.

Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering Sep 11, 2020
The present study represents an original approach to data interpretation of clinical data for patients with diagnosis diabetes mellitus type 2 (DMT2) using fuzzy clustering as a tool for intelligent data analysis. Fuzzy clustering is often used in cl...
Middle Aged Diabetes Mellitus, Type 2 Humans Fuzzy Logic Algorithms Cluster Analysis Male Predictive Value of Tests
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A Comparative Analysis of Two Machine Learning-Based Diagnostic Patterns with Thyroid Imaging Reporting and Data System for Thyroid Nodules: Diagnostic Performance and Unnecessary Biopsy Rate.

Thyroid : official journal of the American Thyroid Association Sep 9, 2020
The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low diagnostic specificity. Machine learning (ML) methods can optimize the diagnostic perf...
Biopsy, Fine-Needle Unnecessary Procedures Elasticity Imaging Techniques Thyroid Nodule Predictive Value of Tests Middle Aged Tumor Burden Aged, 80 and over China Image Interpretation, Computer-Assisted Young Adult Adolescent Retrospective Studies Adult Thyroid Neoplasms Humans Clinical Decision-Making Ultrasonography Male Machine Learning Female Reproducibility of Results Aged
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Personalized prediction of daily eczema severity scores using a mechanistic machine learning model.

Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology Sep 9, 2020
BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalized treatment strategies for AD is challenging, given the apparent unpredictability and large variation in AD symptoms ...
Humans Machine Learning Predictive Value of Tests Bayes Theorem Probability Proof of Concept Study Dermatitis, Atopic Reproducibility of Results Severity of Illness Index Diagnosis, Computer-Assisted Time Factors Treatment Outcome
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Radiomic Model for Distinguishing Dissecting Aneurysms from Complicated Saccular Aneurysms on high-Resolution Magnetic Resonance Imaging.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 8, 2020
OBJECTIVE: To build radiomic model in differentiating dissecting aneurysm (DA) from complicated saccular aneurysm (SA) based on high-resolution magnetic resonance imaging (HR-MRI) through machine-learning algorithm.
Female Reproducibility of Results Aged Adult Humans Male Image Interpretation, Computer-Assisted Machine Learning Aortic Dissection Middle Aged Retrospective Studies Intracranial Aneurysm Magnetic Resonance Imaging Diagnosis, Differential Predictive Value of Tests
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Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential.

Fertility and sterility Sep 8, 2020
OBJECTIVE: To describe novel embryo features capable of predicting implantation potential as input data for an artificial neural network (ANN) model.
Infertility Single Embryo Transfer Oocyte Donation Pregnancy Rate Fertilization in Vitro Neural Networks, Computer Treatment Outcome Embryo Implantation Retrospective Studies Pregnancy Predictive Value of Tests Female Humans Time Factors Blastocyst Fertility Image Interpretation, Computer-Assisted Time-Lapse Imaging
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Development and validation of a model to predict survival in colorectal cancer using a gradient-boosted machine.

Gut Sep 4, 2020
OBJECTIVE: The success of treatment planning relies critically on our ability to predict the potential benefit of a therapy. In colorectal cancer (CRC), several nomograms are available to predict different outcomes based on the use of tumour specific...
Colorectal Neoplasms Male Middle Aged Risk Assessment Predictive Value of Tests Humans Artificial Intelligence Prospective Studies Female Aged Survival Analysis Sigmoidoscopy
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Stacking models for nearly optimal link prediction in complex networks.

Proceedings of the National Academy of Sciences of the United States of America Sep 4, 2020
Most real-world networks are incompletely observed. Algorithms that can accurately predict which links are missing can dramatically speed up network data collection and improve network model validation. Many algorithms now exist for predicting missin...
Neural Networks, Computer Machine Learning Models, Statistical Predictive Value of Tests Social Networking Humans
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ALICE: a hybrid AI paradigm with enhanced connectivity and cybersecurity for a serendipitous encounter with circulating hybrid cells.

Theranostics Sep 2, 2020
A fully automated and accurate assay of rare cell phenotypes in densely-packed fluorescently-labeled liquid biopsy images remains elusive. Employing a hybrid artificial intelligence (AI) paradigm that combines traditional rule-based morphological ma...
Computer Security Image Processing, Computer-Assisted Neoplastic Cells, Circulating Pancreatic Neoplasms Reproducibility of Results Humans Predictive Value of Tests Aged Cell Count Machine Learning Principal Component Analysis Microscopy, Fluorescence Biomarkers, Tumor Software Internet of Things Female Male Liquid Biopsy Middle Aged
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Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.

JAMA network open Sep 1, 2020
IMPORTANCE: The improvement of pulmonary nodule detection, which is a challenging task when using chest radiographs, may help to elevate the role of chest radiographs for the diagnosis of lung cancer.
Sensitivity and Specificity Tumor Burden Male Artificial Intelligence Humans Radiography, Thoracic Lung Neoplasms Algorithms Middle Aged Radiographic Image Enhancement Solitary Pulmonary Nodule Female Lung Early Detection of Cancer Reproducibility of Results Deep Learning Predictive Value of Tests Aged Radiologists
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Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.

European journal of radiology Aug 28, 2020
PURPOSE: To investigate the prediction performance of radiomic models based on multiparametric MRI in predicting the meningioma grade.
Meningeal Neoplasms Male Humans Multiparametric Magnetic Resonance Imaging Middle Aged Machine Learning ROC Curve Neoplasm Grading Retrospective Studies Predictive Value of Tests Image Interpretation, Computer-Assisted Female Area Under Curve Preoperative Care Reproducibility of Results Meningioma
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