AIMC Topic: Logistic Models

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Prediction of Major Complications and Readmission After Lumbar Spinal Fusion: A Machine Learning-Driven Approach.

World neurosurgery May 28, 2021
BACKGROUND: Given the significant cost and morbidity of patients undergoing lumbar fusion, accurate preoperative risk-stratification would be of great utility. We aim to develop a machine learning model for prediction of major complications and readm...
Area Under Curve Machine Learning Spinal Fusion Lumbar Vertebrae Algorithms Patient Readmission Treatment Outcome Humans Retrospective Studies Risk Factors Models, Statistical Female Aged Predictive Value of Tests Risk Assessment Male Middle Aged Postoperative Complications ROC Curve Logistic Models
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Evaluating atypical language in autism using automated language measures.

Scientific reports May 26, 2021
Measurement of language atypicalities in Autism Spectrum Disorder (ASD) is cumbersome and costly. Better language outcome measures are needed. Using language transcripts, we generated Automated Language Measures (ALMs) and tested their validity. 169 ...
Humans Autism Spectrum Disorder Models, Neurological Adolescent Female Diagnosis, Differential Attention Deficit Disorder with Hyperactivity Child Natural Language Processing Language Disorders Male Logistic Models Language Tests Severity of Illness Index Magnetic Resonance Imaging Functional Neuroimaging
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Cost-sensitive learning for semi-supervised hit-and-run analysis.

Accident; analysis and prevention May 25, 2021
Hit-and-run crashes not only degrade the morality, but also result in delays of medical services provided to victims. However, class imbalance problem exists as the number of hit-and-run crashes is much smaller than that of non-hit-and-run crashes. T...
Humans Machine Learning Logistic Models Australia Accidents, Traffic Probability
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Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission.

Computers, informatics, nursing : CIN May 25, 2021
Being bedridden is a frequent comorbid condition that leads to a series of complications in clinical practice. The present study aimed to predict bedridden duration of hospitalized patients based on EMR at admission by machine learning. The medical d...
Logistic Models Humans Machine Learning Support Vector Machine Retrospective Studies Hospitalization
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Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Health care management science May 24, 2021
Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electronic health records (EHR) in particular, collect valuable demographic and clinical patient data from t...
Hospitals Logistic Models Data Mining Humans Machine Learning Electronic Health Records
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Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Biometrical journal. Biometrische Zeitschrift May 24, 2021
Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size is often informative because people receiving more care are less healthy and at higher risk of poor outcomes. We used data from seven health systems ...
Area Under Curve Algorithms Suicide Logistic Models Humans Machine Learning
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Prediction of the risk of C5 palsy after posterior laminectomy and fusion with cervical myelopathy using a support vector machine: an analysis of 184 consecutive patients.

Journal of orthopaedic surgery and research May 21, 2021
BACKGROUND: This study aimed to predict C5 palsy (C5P) after posterior laminectomy and fusion (PLF) with cervical myelopathy (CM) from routinely available variables using a support vector machine (SVM) method.
Humans Forecasting Laminectomy ROC Curve Logistic Models Aged Spinal Fusion Support Vector Machine Male Multivariate Analysis Cervical Vertebrae Retrospective Studies Middle Aged Spinal Cord Diseases Postoperative Complications Female Paralysis Risk Factors
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Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation.

PloS one May 21, 2021
Donor-Recipient (D-R) matching is one of the main challenges to be fulfilled nowadays. Due to the increasing number of recipients and the small amount of donors in liver transplantation, the allocation method is crucial. In this paper, to establish a...
Liver Transplantation Transplant Recipients Logistic Models Tissue and Organ Procurement Humans Support Vector Machine Histocompatibility Testing Databases, Factual Data Interpretation, Statistical Tissue Donors Bayes Theorem
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Prediction of Motor Function in Stroke Patients Using Machine Learning Algorithm: Development of Practical Models.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association May 19, 2021
BACKGROUND: Machine learning (ML) techniques are being increasingly adopted in the medical field.
Diagnosis, Computer-Assisted Deep Learning Time Factors Logistic Models Reproducibility of Results Aged Male Middle Aged Extremities Motor Activity Recovery of Function Predictive Value of Tests Functional Status Stroke Humans Decision Support Techniques Prognosis Retrospective Studies Female
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Prediction of premature all-cause mortality in patients receiving peritoneal dialysis using modified artificial neural networks.

Aging May 13, 2021
Premature all-cause mortality is high in patients receiving peritoneal dialysis (PD). The accurate and early prediction of mortality is critical and difficult. Three prediction models, the logistic regression (LR) model, artificial neural network (AN...
Aged Adult Male Middle Aged Humans Neural Networks, Computer Female Models, Biological Multivariate Analysis ROC Curve Peritoneal Dialysis Logistic Models Mortality, Premature Treatment Outcome Follow-Up Studies
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