AIMC Topic: Logistic Models

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Machine Learning Models for Predicting the Outcomes of Surgical Treatment of Colorectal Liver Metastases.

Journal of the American College of Surgeons
BACKGROUND: Surgical intervention remains the cornerstone of a multidisciplinary approach in the treatment of colorectal liver metastases (CLM). Nevertheless, patient outcomes vary greatly. While predictive tools can assist decision-making and patien...

Long-term care insurance purchase decisions of registered nurses: Deep learning versus logistic regression models.

Health policy (Amsterdam, Netherlands)
OBJECTIVE: The purpose of this study was to use a deep learning model and a traditional statistical regression model to predict the long-term care insurance decisions of registered nurses.

Machine learning prediction of malignant middle cerebral artery infarction after mechanical thrombectomy for anterior circulation large vessel occlusion.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: Prediction of malignant middle cerebral artery infarction (MMI) could identify patients for early intervention. We trained and internally validated a ML model that predicts MMI following mechanical thrombectomy (MT) for ACLVO.

A tree-based modeling approach for matched case-control studies.

Statistics in medicine
Conditional logistic regression (CLR) is the indisputable standard method for the analysis of matched case-control studies. However, CLR is strongly restricted with respect to the inclusion of non-linear effects and interactions of confounding variab...

An Insight into the Machine-Learning-Based Fileless Malware Detection.

Sensors (Basel, Switzerland)
In recent years, massive development in the malware industry changed the entire landscape for malware development. Therefore, cybercriminals became more sophisticated by advancing their development techniques from file-based to fileless malware. As f...

Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.

The British journal of radiology
OBJECTIVES: To precisely predict prostate cancer (PCa) risk stratification, we constructed a machine learning (ML) model based on magnetic resonance imaging (MRI) radiomic features.

Human Activity Recognition for AI-Enabled Healthcare Using Low-Resolution Infrared Sensor Data.

Sensors (Basel, Switzerland)
This paper explores the feasibility of using low-resolution infrared (LRIR) image streams for human activity recognition (HAR) with potential application in e-healthcare. Two datasets based on synchronized multichannel LRIR sensors systems are consid...

Prediction of coronary heart disease in gout patients using machine learning models.

Mathematical biosciences and engineering : MBE
Growing evidence shows that there is an increased risk of cardiovascular diseases among gout patients, especially coronary heart disease (CHD). Screening for CHD in gout patients based on simple clinical factors is still challenging. Here we aim to b...

Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters.

International journal of environmental research and public health
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children's TMC prediction stu...

Development and international validation of logistic regression and machine-learning models for the prediction of 10-year molar loss.

Journal of clinical periodontology
AIM: To develop and validate models based on logistic regression and artificial intelligence for prognostic prediction of molar survival in periodontally affected patients.