AI Medical Compendium Topic:
Logistic Models

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Predicting the Risk of Adverse Events in Pregnant Women With Congenital Heart Disease.

Journal of the American Heart Association Jul 14, 2020
Background Women with congenital heart disease are considered at high risk for adverse events. Therefore, we aim to establish 2 prediction models for mothers and their offspring, which can predict the risk of adverse events occurred in pregnant women...
Humans Machine Learning Pregnancy Female Pregnancy Complications Heart Defects, Congenital Risk Assessment China Adolescent Logistic Models Infant, Newborn Young Adult Adult Middle Aged
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Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI.

The Laryngoscope Jul 13, 2020
OBJECTIVES: To investigate whether a radiomic MRI feature-based prediction model can differentiate oropharyngeal squamous cell carcinoma (SCC) according to the human papillomavirus (HPV) status.
Middle Aged ROC Curve Papillomavirus Infections Logistic Models Squamous Cell Carcinoma of Head and Neck Retrospective Studies Female Aged Male Alphapapillomavirus Magnetic Resonance Imaging Predictive Value of Tests Feasibility Studies Oropharyngeal Neoplasms Humans Machine Learning
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Deep learning approach for prediction of impact peak appearance at ground reaction force signal of running activity.

Computer methods in biomechanics and biomedical engineering Jul 9, 2020
Protruding impact peak is one of the features of vertical ground reaction force (GRF) that is related to injury risk while running. The present research is dedicated to predicting GRF impact peak appearance by setting a binary classification problem....
Humans Neural Networks, Computer Logistic Models Support Vector Machine Cluster Analysis Signal Processing, Computer-Assisted Algorithms Running Deep Learning
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Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

PloS one Jul 8, 2020
OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI).
Young Adult Adult Male Models, Biological Respiration, Artificial Logistic Models Humans Treatment Outcome Brain Injuries, Traumatic Machine Learning Registries Prognosis Female
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Machine learning for pattern detection in cochlear implant FDA adverse event reports.

Cochlear implants international Jul 5, 2020
Medical device performance and safety databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design. The objective of this analysis was to use supervised machine learning to explore patterns in rep...
Algorithms Databases, Factual Female Adult Male Humans Machine Learning United States Food and Drug Administration Cochlear Implantation Equipment Failure Analysis Cochlear Implants Public Reporting of Healthcare Data Child Logistic Models United States Bayes Theorem
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Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jun 30, 2020
OBJECTIVE: To determine whether machine learning (ML) can predict the presence of extracapsular extension (ECE) prior to treatment, using common oncologic variables, in patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell c...
Machine Learning Databases, Factual Prognosis Retrospective Studies Male Female Humans Alphapapillomavirus Papillomavirus Infections Aged Middle Aged Extranodal Extension Logistic Models ROC Curve Squamous Cell Carcinoma of Head and Neck Oropharyngeal Neoplasms
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Don't dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning.

BMC medical research methodology Jun 29, 2020
BACKGROUND: Machine learning approaches have become increasingly popular modeling techniques, relying on data-driven heuristics to arrive at its solutions. Recent comparisons between these algorithms and traditional statistical modeling techniques ha...
Algorithms Logistic Models Models, Statistical Humans Machine Learning
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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 (...
Tuberculosis Sex Factors Diagnostic Tests, Routine Solitary Pulmonary Nodule Tomography, X-Ray Computed Adenocarcinoma of Lung Observer Variation Lung Neoplasms Regression Analysis Female Pattern Recognition, Automated Logistic Models Diagnosis, Differential Adult Calibration Nomograms Granuloma Male Age Factors Humans Deep Learning Middle Aged Algorithms Diagnosis, Computer-Assisted ROC Curve Retrospective Studies Image Processing, Computer-Assisted
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An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

BioMed research international Jun 27, 2020
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...
ROC Curve Female Lung Neoplasms Carcinoma, Non-Small-Cell Lung Models, Biological Reproducibility of Results Bone Neoplasms Humans Logistic Models Survival Analysis Aged Artificial Intelligence Nomograms Multivariate Analysis Male Algorithms Prognosis
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Logistic regression with image covariates via the combination of L1 and Sobolev regularizations.

PloS one Jun 26, 2020
The use of image covariates to build a classification model has lots of impact in various fields, such as computer science, medicine, and so on. The aim of this paper is to develop an estimation method for logistic regression model with image covaria...
Likelihood Functions Phantoms, Imaging Machine Learning Computer Simulation Image Processing, Computer-Assisted Logistic Models
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