AIMC Topic: Logistic Models

Clear Filters Showing 711 to 720 of 1261 articles

Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease Jun 8, 2020
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...
Area Under Curve Bayes Theorem Tertiary Care Centers Clostridium Infections Clostridioides difficile Middle Aged Diarrhea ROC Curve Logistic Models Humans Anti-Bacterial Agents Machine Learning Retrospective Studies Forecasting Female Aged Male
View on PubMed DOI

An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BMC bioinformatics Jun 8, 2020
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and accounts for cancer-related deaths. Survival rates are very low when the tumor is discovered in the late-stage. Thus, developing an efficient s...
Area Under Curve Neoplasm Staging RNA Kidney Neoplasms Carcinoma, Renal Cell Humans Machine Learning Female ROC Curve Logistic Models
View on PubMed DOI

Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

PloS one May 29, 2020
BACKGROUND: Although dialysis patients are at a high risk of death, it is difficult for medical practitioners to simultaneously evaluate many inter-related risk factors. In this study, we evaluated the characteristics of hemodialysis patients using m...
Artificial Intelligence Adult Female Japan Cohort Studies Humans Machine Learning Male Risk Factors Middle Aged Logistic Models Databases, Factual Decision Making, Computer-Assisted Aged Deep Learning Support Vector Machine Prospective Studies Aged, 80 and over Renal Dialysis Cluster Analysis Prognosis Kidney Failure, Chronic
View on PubMed DOI

A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health May 24, 2020
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...
Logistic Models United States Medicare Appointments and Schedules Ambulatory Care Female Aged Male Time Factors Humans Neural Networks, Computer Machine Learning
View on PubMed DOI

Osteoporotic hip fracture prediction from risk factors available in administrative claims data - A machine learning approach.

PloS one May 19, 2020
OBJECTIVE: Hip fractures are among the most frequently occurring fragility fractures in older adults, associated with a loss of quality of life, high mortality, and high use of healthcare resources. The aim was to apply the superlearner method to pre...
Germany Osteoporotic Fractures Humans Aged, 80 and over Machine Learning Male Algorithms Logistic Models Nonlinear Dynamics Hip Fractures Retrospective Studies Female Risk Factors Aged
View on PubMed DOI

Artificial Intelligence Models Predict Operative Versus Nonoperative Management of Patients with Adult Spinal Deformity with 86% Accuracy.

World neurosurgery May 17, 2020
OBJECTIVE: Patients with ASD show complex and highly variable disease. The decision to manage patients operatively is largely subjective and varies based on surgeon training and experience. We sought to develop models capable of accurately discrimina...
Scoliosis Congenital Abnormalities Humans Artificial Intelligence Retrospective Studies Female Adult Male Middle Aged Quality of Life Logistic Models Linear Models
View on PubMed DOI

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

Computational and mathematical methods in medicine May 16, 2020
In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) signal analysis methods, using EEG signals to monitor human health has become a very popular research fi...
Brain Waves Fatigue Head Movements Ocular Physiological Phenomena Logistic Models Support Vector Machine Electroencephalography Signal Processing, Computer-Assisted Wavelet Analysis Humans Neural Networks, Computer Algorithms Computational Biology
View on PubMed DOI

Applying machine learning methods to develop a successful aging maintenance prediction model based on physical fitness tests.

Geriatrics & gerontology international May 1, 2020
AIM: The purpose of this study was to develop a machine learning prediction model for successful aging (SA) based on physical fitness tests.
Sensitivity and Specificity Male Aging Middle Aged Exercise Humans Machine Learning Female Aged Aged, 80 and over Independent Living Healthy Aging Follow-Up Studies Decision Trees Predictive Value of Tests Geriatric Assessment Physical Fitness China Surveys and Questionnaires ROC Curve Logistic Models
View on PubMed DOI

Machine learning approaches to predict peak demand days of cardiovascular admissions considering environmental exposure.

BMC medical informatics and decision making May 1, 2020
BACKGROUND: Accumulating evidence has linked environmental exposure, such as ambient air pollution and meteorological factors, to the development and severity of cardiovascular diseases (CVDs), resulting in increased healthcare demand. Effective pred...
Hospitalization China Logistic Models Support Vector Machine Environmental Exposure Humans Machine Learning
View on PubMed DOI

Development and validation of machine learning prediction model based on computed tomography angiography-derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study.

European radiology Apr 29, 2020
OBJECTIVES: To build models based on conventional logistic regression (LR) and machine learning (ML) algorithms combining clinical, morphological, and hemodynamic information to predict individual rupture status of unruptured intracranial aneurysms (...
Humans Neural Networks, Computer Machine Learning Computer Simulation Retrospective Studies Tomography, X-Ray Computed Support Vector Machine Female Area Under Curve Aged Computed Tomography Angiography Middle Aged Aged, 80 and over Intracranial Aneurysm Cerebral Angiography Hemodynamics Young Adult Aneurysm, Ruptured Clinical Decision Rules China Adult Adolescent Male Logistic Models
View on PubMed DOI
Popular Topics
Recent Journals