AIMC Topic: Algorithms

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Analysis of heterogeneous genomic samples using image normalization and machine learning.

BMC genomics
BACKGROUND: Analysis of heterogeneous populations such as viral quasispecies is one of the most challenging bioinformatics problems. Although machine learning models are becoming to be widely employed for analysis of sequence data from such populatio...

Prediction of out-of-pocket health expenditures in Rwanda using machine learning techniques.

The Pan African medical journal
INTRODUCTION: in Rwanda, the estimated out-of-pocket health expenditure has been increased from 24.46% in 2000 to 26% in 2015. Despite the existence of guideline in estimation of out-of-pocket health expenditures provided by WHO (2018), the estimatio...

RAM-PGK: Prediction of Lysine Phosphoglycerylation Based on Residue Adjacency Matrix.

Genes
BACKGROUND: Post-translational modification (PTM) is a biological process that is associated with the modification of proteome, which results in the alteration of normal cell biology and pathogenesis. There have been numerous PTM reports in recent ye...

Development and evaluation of deep learning for screening dental caries from oral photographs.

Oral diseases
OBJECTIVES: To develop and evaluate the performance of a deep learning system based on convolutional neural network (ConvNet) to detect dental caries from oral photographs.

Particle Swarm Optimization aided PID gait controller design for a humanoid robot.

ISA transactions
Gait planning for the humanoid robot is a very essential and basic requirement. The humanoid robot is balanced at two feet; therefore, special attention is required for gait analysis for the execution of assigned tasks. In this paper, the linear inve...

Image registration: Maximum likelihood, minimum entropy and deep learning.

Medical image analysis
In this work, we propose a theoretical framework based on maximum profile likelihood for pairwise and groupwise registration. By an asymptotic analysis, we demonstrate that maximum profile likelihood registration minimizes an upper bound on the joint...

Deep learning algorithms for brain disease detection with magnetic induction tomography.

Medical physics
PURPOSE: In order to improve the reconstruction accuracy of magnetic induction tomography (MIT) and achieve fast imaging especially in the detection of cerebral hemorrhage, artificial intelligence algorithms are proposed to improve the accuracy of MI...

Multi-task learning for the simultaneous reconstruction of the human and mouse gene regulatory networks.

Scientific reports
The reconstruction of Gene Regulatory Networks (GRNs) from gene expression data, supported by machine learning approaches, has received increasing attention in recent years. The task at hand is to identify regulatory links between genes in a network....

A deep neural network for estimating the bladder boundary using electrical impedance tomography.

Physiological measurement
OBJECTIVE: Accurate bladder size estimation is an important clinical parameter that assists physicians, enabling them to provide better treatment for patients who are suffering from urinary incontinence. Electrical impedance tomography (EIT) is a non...