AIMC Topic: Regression Analysis

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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...

Moisture Damage Modeling in Lime and Chemically Modified Asphalt at Nanolevel Using Ensemble Computational Intelligence.

Computational intelligence and neuroscience
This paper measures the adhesion/cohesion force among asphalt molecules at nanoscale level using an Atomic Force Microscopy (AFM) and models the moisture damage by applying state-of-the-art Computational Intelligence (CI) techniques (e.g., artificial...

Classifying Acute Ischemic Stroke Onset Time using Deep Imaging Features.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Models have been developed to predict stroke outcomes (e.g., mortality) in attempt to provide better guidance for stroke treatment. However, there is little work in developing classification models for the problem of unknown time-since-stroke (TSS), ...

Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model.

IEEE transactions on bio-medical engineering
Brain-wide and genome-wide association (BW-GWA) study is presented in this paper to identify the associations between the brain imaging phenotypes (i.e., regional volumetric measures) and the genetic variants [i.e., single nucleotide polymorphism (SN...

Robust Regression Estimation Based on Low-Dimensional Recurrent Neural Networks.

IEEE transactions on neural networks and learning systems
The robust Huber's M-estimator is widely used in signal and image processing, classification, and regression. From an optimization point of view, Huber's M-estimation problem is often formulated as a large-sized quadratic programming (QP) problem in ...

Relative location prediction in CT scan images using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and spee...

Pulling force prediction using neural networks.

International journal of occupational safety and ergonomics : JOSE
PURPOSE: In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recent...

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

Talanta
The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by ho...