AIMC Topic: Logistic Models

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A Self-Representation-Based Fuzzy SVM Model for Predicting Vascular Calcification of Hemodialysis Patients.

Computational and mathematical methods in medicine Jul 27, 2021
In end-stage renal disease (ESRD), vascular calcification risk factors are essential for the survival of hemodialysis patients. To effectively assess the level of vascular calcification, the machine learning algorithm can be used to predict the vascu...
Male Algorithms Middle Aged Heart Disease Risk Factors Logistic Models Renal Dialysis Humans Female Aorta, Abdominal Computational Biology Aged Support Vector Machine Neural Networks, Computer Vascular Calcification Adult Fuzzy Logic Machine Learning Kidney Failure, Chronic
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Preliminary study on the application of renal ultrasonography radiomics in the classification of glomerulopathy.

BMC medical imaging Jul 23, 2021
BACKGROUND: The aim of this study was to investigate the potential use of renal ultrasonography radiomics features in the histologic classification of glomerulopathy.
Ultrasonography ROC Curve Kidney Logistic Models Diagnosis, Differential Humans Female Glomerulonephritis, IGA Machine Learning Glomerulonephritis, Membranous Adult Algorithms Glomerulonephritis Male Middle Aged
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Machine learning-based preoperative datamining can predict the therapeutic outcome of sleep surgery in OSA subjects.

Scientific reports Jul 21, 2021
Increasing recognition of anatomical obstruction has resulted in a large variety of sleep surgeries to improve anatomic collapse of obstructive sleep apnea (OSA) and the prediction of whether sleep surgery will have successful outcome is very importa...
Sleep Apnea, Obstructive Preoperative Period Otorhinolaryngologic Surgical Procedures Oropharynx Middle Aged Logistic Models Treatment Outcome Humans Machine Learning Female Adult Male
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Development of Machine Learning Models for Prediction of Osteoporosis from Clinical Health Examination Data.

International journal of environmental research and public health Jul 18, 2021
Osteoporosis is treatable but often overlooked in clinical practice. We aimed to construct prediction models with machine learning algorithms to serve as screening tools for osteoporosis in adults over fifty years old. Additionally, we also compared ...
Middle Aged Logistic Models Taiwan Osteoporosis Female Adult Male Humans Neural Networks, Computer Machine Learning
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Identifying mislabelled samples: Machine learning models exceed human performance.

Annals of clinical biochemistry Jul 16, 2021
BACKGROUND: It is difficult for clinical laboratories to identify samples that are labelled with the details of an incorrect patient. Many laboratories screen for these errors with delta checks, with final decision-making based on manual review of re...
Machine Learning Algorithms Computer Simulation Logistic Models Humans Neural Networks, Computer Support Vector Machine Laboratories, Clinical
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Predicting self-intercepted medication ordering errors using machine learning.

PloS one Jul 14, 2021
Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to mis...
Medication Errors Humans Machine Learning Medical Order Entry Systems Child Female Middle Aged ROC Curve Aged Aged, 80 and over Infant Logistic Models Adolescent Young Adult Child, Preschool Adult Male
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CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

Stroke Jul 9, 2021
BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and appl...
Humans Machine Learning Middle Aged ROC Curve Subarachnoid Hemorrhage Logistic Models Aged Treatment Outcome Young Adult Support Vector Machine Prognosis Models, Statistical Adult Female Predictive Value of Tests Male Reproducibility of Results C-Reactive Protein
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Understand the impact of traffic states on crash risk in the vicinities of Type A weaving segments: A deep learning approach.

Accident; analysis and prevention Jul 9, 2021
The primary objective of this study was to evaluate the impacts of traffic states on crash risk in the vicinities of Type A weaving segments. A deep convolutional embedded clustering (DCEC) was developed to classify traffic flow into nine states. The...
Cluster Analysis Accidents, Traffic Humans Neural Networks, Computer Deep Learning Logistic Models
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Using machine learning to predict severe hypoglycaemia in hospital.

Diabetes, obesity & metabolism Jul 8, 2021
AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients.
Retrospective Studies Hospitals Logistic Models Hypoglycemia Humans Machine Learning
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Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey.

Biosensors Jul 8, 2021
Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. This paper aims to develop a model that predicts the prevalence of cardiovascular disease using health...
Machine Learning Algorithms Republic of Korea Cardiovascular Diseases Wearable Electronic Devices Logistic Models Nutrition Surveys Support Vector Machine Humans Neural Networks, Computer
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