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Linear Models

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Comparing Prediction of Early TBI Mortality with Multilayer Perceptron Neural Network and Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we compare the performance of a multilayer perceptron neural network and convolutional networks for the prediction of 14-day mortality in patients with TBI, using a database obtained in a low-and middle-income country, with 529 records ...

Estimation of Low-Density Lipoprotein Cholesterol Concentration Using Machine Learning.

Laboratory medicine
OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Martin-Hopkins formulas. We developed LDL-C prediction models using multiple machine learning methods and investigated the validity of the new models alo...

Simple Linear Cancer Risk Prediction Models With Novel Features Outperform Complex Approaches.

JCO clinical cancer informatics
PURPOSE: The ability to accurately predict an individual's risk for cancer is critical to the implementation of precision prevention measures. Current cancer risk predictions are frequently made with simple models that use a few proven risk factors, ...

Foundations of Machine Learning-Based Clinical Prediction Modeling: Part V-A Practical Approach to Regression Problems.

Acta neurochirurgica. Supplement
This chapter goes through the steps required to train and validate a simple, machine learning-based clinical prediction model for any continuous outcome. We supply fully structured code for the readers to download and execute in parallel to this sect...

Application of supervised machine learning as a method for identifying DEM contact law parameters.

Mathematical biosciences and engineering : MBE
Calibration of Discrete Element Method (DEM) models is an iterative process of adjusting input parameters such that the macroscopic results of simulations and experiments are similar. Therefore, selecting appropriate input parameters of a model effec...

Disentangling data dependency using cross-validation strategies to evaluate prediction quality of cattle grazing activities using machine learning algorithms and wearable sensor data.

Journal of animal science
Wearable sensors have been explored as an alternative for real-time monitoring of cattle feeding behavior in grazing systems. To evaluate the performance of predictive models such as machine learning (ML) techniques, data cross-validation (CV) approa...

Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach.

American journal of epidemiology
The human diet consists of a complex mixture of components. To realistically assess dietary impacts on health, new statistical tools that can better address nonlinear, collinear, and interactive relationships are necessary. Using data from 1,928 heal...

Applications of Artificial Intelligence for Retinopathy of Prematurity Screening.

Pediatrics
OBJECTIVES: Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based screening in an Indian ROP telemedicine pr...

Reflection on modern methods: generalized linear models for prognosis and intervention-theory, practice and implications for machine learning.

International journal of epidemiology
Prediction and causal explanation are fundamentally distinct tasks of data analysis. In health applications, this difference can be understood in terms of the difference between prognosis (prediction) and prevention/treatment (causal explanation). Ne...

Prediction of tuberculosis cases based on sociodemographic and environmental factors in gombak, Selangor, Malaysia: A comparative assessment of multiple linear regression and artificial neural network models.

International journal of mycobacteriology
BACKGROUND: Early prediction of tuberculosis (TB) cases is very crucial for its prevention and control. This study aims to predict the number of TB cases in Gombak based on sociodemographic and environmental factors.