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Logistic Models

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Gradient boosted trees with individual explanations: An alternative to logistic regression for viability prediction in the first trimester of pregnancy.

Computer methods and programs in biomedicine
BACKGROUND: Clinical models to predict first trimester viability are traditionally based on multivariable logistic regression (LR) which is not directly interpretable for non-statistical experts like physicians. Furthermore, LR requires complete data...

Survival prediction among heart patients using machine learning techniques.

Mathematical biosciences and engineering : MBE
Cardiovascular diseases are regarded as the most common reason for worldwide deaths. As per World Health Organization, nearly 17.9 million people die of heart-related diseases each year. The high shares of cardiovascular-related diseases in total wor...

Natural language processing of head CT reports to identify intracranial mass effect: CTIME algorithm.

The American journal of emergency medicine
BACKGROUND: The Mortality Probability Model (MPM) is used in research and quality improvement to adjust for severity of illness and can also inform triage decisions. However, a limitation for its automated use or application is that it includes the v...

Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.

Journal of Korean medical science
BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.

Identification of diagnostic signatures in ulcerative colitis patients via bioinformatic analysis integrated with machine learning.

Human cell
Ulcerative colitis (UC) is an immune-related disorder with enhanced prevalence globally. Early diagnosis is critical for the effective treatment of UC. However, it still lacks specific diagnostic signatures. The aim of our study was to explore effici...

Building a predictive model to assist in the diagnosis of cervical cancer.

Future oncology (London, England)
Cervical cancer is still one of the most common gynecologic cancers in the world. Since cervical cancer is a potentially preventive cancer, earlier detection is the most effective technique for decreasing the worldwide incidence of the illness. Thi...

Predicting the Cochlear Dead Regions Using a Machine Learning-Based Approach with Oversampling Techniques.

Medicina (Kaunas, Lithuania)
: Determining the presence or absence of cochlear dead regions (DRs) is essential in clinical practice. This study proposes a machine learning (ML)-based model that applies oversampling techniques for predicting DRs in patients. : We used recursive p...

Machine learning techniques for mortality prediction in emergency departments: a systematic review.

BMJ open
OBJECTIVES: This systematic review aimed to assess the performance and clinical feasibility of machine learning (ML) algorithms in prediction of in-hospital mortality for medical patients using vital signs at emergency departments (EDs).

Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018.

Psychiatry research
Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depressi...

Effects of dataset size and interactions on the prediction performance of logistic regression and deep learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Machine learning and deep learning models are very powerful in predicting the presence of a disease. To achieve good predictions, those models require a certain amount of data to train on, whereas this amount i) is generally...