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Regression Analysis

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Application of Artificial Neural Network in miRNA Biomarker Selection and Precise Diagnosis of Colorectal Cancer.

Iranian biomedical journal
BACKGROUND: The early diagnosis of colorectal cancer (CRC) is associated with improved survival rates, and development of novel non-invasive, sensitive, and specific diagnostic tests is highly demanded. The objective of this paper was to identify com...

Modeling the covariates effects on the hazard function by piecewise exponential artificial neural networks: an application to a controlled clinical trial on renal carcinoma.

BMC bioinformatics
BACKGROUND: In exploring the time course of a disease to support or generate biological hypotheses, the shape of the hazard function provides relevant information. For long follow-ups the shape of hazard function may be complex, with the presence of ...

Nonparallel support vector regression model and its SMO-type solver.

Neural networks : the official journal of the International Neural Network Society
Although the twin support vector regression (TSVR) method has been widely studied and various variants are successfully developed, the structural risk minimization (SRM) principle and model's sparseness are not given sufficient consideration. In this...

Prediction task guided representation learning of medical codes in EHR.

Journal of biomedical informatics
There have been rapidly growing applications using machine learning models for predictive analytics in Electronic Health Records (EHR) to improve the quality of hospital services and the efficiency of healthcare resource utilization. A fundamental an...

Fetal health status prediction based on maternal clinical history using machine learning techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Congenital anomalies are seen at 1-3% of the population, probabilities of which are tried to be found out primarily through double, triple and quad tests during pregnancy. Also, ultrasonographical evaluations of fetuses enha...

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

Statistics in medicine
Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric...

A bioavailable strontium isoscape for Western Europe: A machine learning approach.

PloS one
Strontium isotope ratios (87Sr/86Sr) are gaining considerable interest as a geolocation tool and are now widely applied in archaeology, ecology, and forensic research. However, their application for provenance requires the development of baseline mod...

Exploiting semantic patterns over biomedical knowledge graphs for predicting treatment and causative relations.

Journal of biomedical informatics
BACKGROUND: Identifying new potential treatment options for medical conditions that cause human disease burden is a central task of biomedical research. Since all candidate drugs cannot be tested with animal and clinical trials, in vitro approaches a...

Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach.

Computers in biology and medicine
The optical properties of blood play crucial roles in medical diagnostics and treatment, and in the design of new medical devices. Haemoglobin is a vital constituent of the blood whose optical properties affect all of the optical properties of human ...

Recurrent Shape Regression.

IEEE transactions on pattern analysis and machine intelligence
An end-to-end network architecture, the Recurrent Shape Regression (RSR), is presented to deal with the task of facial shape detection, a crucial step in many computer vision problems. The RSR generalizes the conventional cascaded regression into a r...