AIMC Topic: Algorithms

Clear Filters Showing 20971 to 20980 of 28713 articles

Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications.

Journal of molecular biology
Understanding the genetic basis of complex diseases is challenging. Prior work shows that disease-related proteins do not typically function in isolation. Rather, they often interact with each other to form a network module that underlies dysfunction...

Analysis of hepatitis B virus infection in blood sera using Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy
This study presents the analysis of hepatitis B virus (HBV) infection in human blood serum using Raman spectroscopy combined with pattern recognition technique. In total, 119 confirmed samples of HBV infected sera, collected from Pakistan Atomic Ener...

Optimal two-stage dynamic treatment regimes from a classification perspective with censored survival data.

Biometrics
Clinicians often make multiple treatment decisions at key points over the course of a patient's disease. A dynamic treatment regime is a sequence of decision rules, each mapping a patient's observed history to the set of available, feasible treatment...

Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net.

Medical image analysis
Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-c...

Experimental Comparisons of Sparse Dictionary Learning and Independent Component Analysis for Brain Network Inference From fMRI Data.

IEEE transactions on bio-medical engineering
In this work, we conduct comprehensive comparisons between four variants of independent component analysis (ICA) methods and three variants of sparse dictionary learning (SDL) methods, both at the subject-level, by using synthesized fMRI data with gr...

Assessment of the generalization of learned image reconstruction and the potential for transfer learning.

Magnetic resonance in medicine
PURPOSE: Although deep learning has shown great promise for MR image reconstruction, an open question regarding the success of this approach is the robustness in the case of deviations between training and test data. The goal of this study is to asse...

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

Computers in biology and medicine
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic sei...

DPP-PseAAC: A DNA-binding protein prediction model using Chou's general PseAAC.

Journal of theoretical biology
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting...

Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

Journal of neuro-oncology
INTRODUCTION: Machine learning methods have been introduced as a computer aided diagnostic tool, with applications to glioma characterisation on MRI. Such an algorithmic approach may provide a useful adjunct for a rapid and accurate diagnosis of a gl...

Deep Patient Similarity Learning for Personalized Healthcare.

IEEE transactions on nanobioscience
Predicting patients' risk of developing certain diseases is an important research topic in healthcare. Accurately identifying and ranking the similarity among patients based on their historical records is a key step in personalized healthcare. The el...