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Logistic Models

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Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

Journal of the American College of Radiology : JACR
OBJECTIVE: Legislation in 38 states requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit mammographic sensitivity. Because radiologist density assessments vary wid...

Optimizing acute stroke outcome prediction models: Comparison of generalized regression neural networks and logistic regressions.

PloS one
BACKGROUND: Generalized regression neural network (GRNN) and logistic regression (LR) are extensively used in the medical field; however, the better model for predicting stroke outcome has not been established. The primary goal of this study was to c...

Prediction models for early diagnosis of actinomycotic osteomyelitis of the jaw using machine learning techniques: a preliminary study.

BMC oral health
BACKGROUND: This study aimed to develop and validate five machine learning models designed to predict actinomycotic osteomyelitis of the jaw. Furthermore, this study determined the relative importance of the predictive variables for actinomycotic ost...

Development and Validation of an Explainable Machine Learning Model for Major Complications After Cytoreductive Surgery.

JAMA network open
IMPORTANCE: Cytoreductive surgery (CRS) is one of the most complex operations in surgical oncology with significant morbidity, and improved risk prediction tools are critically needed. Machine learning models can potentially overcome the limitations ...

Machine Learning-Assisted Preoperative Diagnosis of Infection Stones in Urolithiasis Patients.

Journal of endourology
The decision-making of how to treat urinary infection stones was complicated by the difficulty in preoperative diagnosis of these stones. Hence, we developed machine learning (ML) models that can be leveraged to discriminate between infection and no...

Dementia risk predictions from German claims data using methods of machine learning.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: We examined whether German claims data are suitable for dementia risk prediction, how machine learning (ML) compares to classical regression, and what the important predictors for dementia risk are.

Predicting Sepsis Mortality in a Population-Based National Database: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Although machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algor...

AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data.

Journal of biomedical informatics
BACKGROUND: Medical decision-making impacts both individual and public health. Clinical scores are commonly used among various decision-making models to determine the degree of disease deterioration at the bedside. AutoScore was proposed as a useful ...

Machine learning versus logistic regression for prognostic modelling in individuals with non-specific neck pain.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: Prognostic models play an important clinical role in the clinical management of neck pain disorders. No study has compared the performance of modern machine learning (ML) techniques, against more traditional regression techniques, when devel...

Epidemiological predictive modeling: lessons learned from the Kuopio ischemic heart disease risk factor study.

Annals of epidemiology
PURPOSE: The use of predictive models in epidemiology is relatively narrow as most of the studies report results of traditional statistical models such as Linear, Logistic, or Cox regressions. In this study, a high-dimensional epidemiological cohort,...