AI Medical Compendium Topic:
Logistic Models

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Machine learning to assist risk-of-bias assessments in systematic reviews.

International journal of epidemiology
BACKGROUND: Risk-of-bias assessments are now a standard component of systematic reviews. At present, reviewers need to manually identify relevant parts of research articles for a set of methodological elements that affect the risk of bias, in order t...

The relationship of blood transfusion with peri-operative and long-term outcomes after major hepatectomy for metastatic colorectal cancer: a multi-institutional study of 456 patients.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: Data on prognostic implications of peri-operative blood transfusion around resection of colorectal cancer liver metastases (CRLM) are conflicting. This retrospective study assesses the association of transfusion with complications and dis...

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

International journal of radiation oncology, biology, physics
Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both pr...

Gene and sample selection using T-score with sample selection.

Journal of biomedical informatics
Gene selection from high-dimensional microarray gene-expression data is statistically a challenging problem. Filter approaches to gene selection have been popular because of their simplicity, efficiency, and accuracy. Due to small sample size, all sa...

Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Digestive diseases and sciences
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...

Pregnancy risk factors in autism: a pilot study with artificial neural networks.

Pediatric research
BACKGROUND: Autism is a multifactorial condition in which a single risk factor can unlikely provide comprehensive explanation for the disease origin. Moreover, due to the complexity of risk factors interplay, traditional statistics is often unable to...

A novel fuzzy logic-based image steganography method to ensure medical data security.

Computers in biology and medicine
This study aims to secure medical data by combining them into one file format using steganographic methods. The electroencephalogram (EEG) is selected as hidden data, and magnetic resonance (MR) images are also used as the cover image. In addition to...

Prediction of delayed graft function after kidney transplantation: comparison between logistic regression and machine learning methods.

BMC medical informatics and decision making
BACKGROUND: Predictive models for delayed graft function (DGF) after kidney transplantation are usually developed using logistic regression. We want to evaluate the value of machine learning methods in the prediction of DGF.

Characterization and machine learning prediction of allele-specific DNA methylation.

Genomics
A large collection of Single Nucleotide Polymorphisms (SNPs) has been identified in the human genome. Currently, the epigenetic influences of SNPs on their neighboring CpG sites remain elusive. A growing body of evidence suggests that locus-specific ...

Tuberculous Pericarditis is Multibacillary and Bacterial Burden Drives High Mortality.

EBioMedicine
BACKGROUND: Tuberculous pericarditis is considered to be a paucibacillary process; the large pericardial fluid accumulation is attributed to an inflammatory response to tuberculoproteins. Mortality rates are high. We investigated the role of clinical...