AIMC Topic: Sex Factors

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Temporal Trends in Cervical Spine Curvature of South Korean Adults Assessed by Deep Learning System Segmentation, 2006-2018.

JAMA network open Oct 1, 2020
IMPORTANCE: The loss of the physiologic cervical lordotic curve is a common degenerative disorder known to be associated with abnormal spinal alignment. However, the changing trends among sex and age groups has not yet been well established.
Humans Retrospective Studies Republic of Korea Deep Learning Age Factors Cervical Vertebrae Sex Factors Kyphosis Lordosis Spinal Curvatures Female Young Adult Adult Cross-Sectional Studies Male Middle Aged
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Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients.

European radiology Sep 18, 2020
OBJECTIVE: To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19.
Proportional Hazards Models Radiography, Thoracic Mortality Radiography Emergency Service, Hospital Italy Tomography, X-Ray Computed Neurodegenerative Diseases Humans Intensive Care Units Pulmonary Disease, Chronic Obstructive Coronary Artery Disease Artificial Intelligence Female Male Sex Factors COVID-19 SARS-CoV-2 Middle Aged Prognosis Hospitalization Comorbidity Retrospective Studies Aged Severity of Illness Index Deep Learning Age Factors
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Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an international multicentre study.

The European respiratory journal Aug 20, 2020
BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality.
Reproducibility of Results Hospitalization Aged Adult Male Middle Aged Humans Machine Learning Pandemics COVID-19 Retrospective Studies Female Decision Support Systems, Clinical Age Factors Predictive Value of Tests Triage Area Under Curve Italy Coronavirus Infections Risk Assessment Severity of Illness Index China Cohort Studies Hospital Mortality ROC Curve Pneumonia, Viral COVID-19 Testing Sex Factors Survival Analysis Internationality Belgium Clinical Laboratory Techniques
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The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms.

Accident; analysis and prevention Jul 2, 2020
In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were applied to the classification of cyclist injury-severity in bicycle-vehicle accidents. The study aims to...
Humans Fuzzy Logic Accidents, Traffic Sex Factors Injury Severity Score Built Environment Bicycling
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An artificial neural network approach for predicting hypertension using NHANES data.

Scientific reports Jun 30, 2020
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabetes in hypertensive patients. It also shows that artificial neural network techniques applied to larg...
Humans Models, Statistical Sex Factors Smoking Male Neural Networks, Computer Middle Aged Algorithms Nutrition Surveys Hypertension Female Body Mass Index Risk Factors Age Factors Adult Sensitivity and Specificity
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Diagnostic Tests, Routine Observer Variation Pattern Recognition, Automated Calibration Adenocarcinoma of Lung Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Solitary Pulmonary Nodule Female ROC Curve Regression Analysis Adult Diagnosis, Differential Image Processing, Computer-Assisted Male Granuloma Middle Aged Lung Neoplasms Tuberculosis Diagnosis, Computer-Assisted Logistic Models Sex Factors Deep Learning Nomograms Age Factors
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Deep learning-based survival prediction for multiple cancer types using histopathology images.

PloS one Jun 17, 2020
Providing prognostic information at the time of cancer diagnosis has important implications for treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and clinical variables can provide useful prognostic ...
Sex Factors Survival Analysis Humans Datasets as Topic Neoplasms Female Deep Learning Prognosis Risk Factors Image Processing, Computer-Assisted Adult Age Factors Male Neoplasm Staging Middle Aged Feasibility Studies Risk Assessment
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Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis.

Proceedings of the National Academy of Sciences of the United States of America May 26, 2020
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening are being adopted worldwide by medical institutions. In such a context, generating fair and unbiased classifiers becomes of paramount importance. The research...
Humans Female Male Deep Learning Bias Radiographic Image Interpretation, Computer-Assisted Sex Factors Datasets as Topic Reference Standards Radiography, Thoracic
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Psychosocial profiles and their predictors in epilepsy using patient-reported outcomes and machine learning.

Epilepsia May 20, 2020
OBJECTIVE: To apply unsupervised machine learning to patient-reported outcomes to identify clusters of epilepsy patients exhibiting unique psychosocial characteristics.
Sex Factors Age of Onset Humans Patient Reported Outcome Measures Quality of Life Psychology Female Socioeconomic Factors Adult Age Factors Cross-Sectional Studies Cluster Analysis Male Middle Aged Unsupervised Machine Learning Epilepsy
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Development and Validation of Machine Learning Algorithms for Predicting Adverse Events After Surgery for Lumbar Degenerative Spondylolisthesis.

World neurosurgery Apr 25, 2020
BACKGROUND: Preoperative prognostication of adverse events (AEs) for patients undergoing surgery for lumbar degenerative spondylolisthesis (LDS) can improve risk stratification and help guide the surgical decision-making process. The aim of this stud...
Clinical Decision Rules Sex Factors Transplantation, Autologous Bone Transplantation Ilium Humans Serum Albumin Machine Learning Spondylolisthesis Adult Decision Making Algorithms Male Functional Status Prognosis Neurosurgical Procedures Middle Aged Female Spinal Fusion Postoperative Complications Risk Factors Lumbar Vertebrae Adolescent Aged Alkaline Phosphatase Logistic Models Aged, 80 and over Age Factors Young Adult
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