AIMC Topic: Algorithms

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Prioritising references for systematic reviews with RobotAnalyst: A user study.

Research synthesis methods
Screening references is a time-consuming step necessary for systematic reviews and guideline development. Previous studies have shown that human effort can be reduced by using machine learning software to prioritise large reference collections such t...

Crowdsourcing image analysis for plant phenomics to generate ground truth data for machine learning.

PLoS computational biology
The accuracy of machine learning tasks critically depends on high quality ground truth data. Therefore, in many cases, producing good ground truth data typically involves trained professionals; however, this can be costly in time, effort, and money. ...

3-D Neural denoising for low-dose Coronary CT Angiography (CCTA).

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. However, it exposes the patient to significant radiation doses, resulting from high image quality requirements and acquisitions at multiple cardiac ph...

An unsupervised machine learning method for discovering patient clusters based on genetic signatures.

Journal of biomedical informatics
INTRODUCTION: Many chronic disorders have genomic etiology, disease progression, clinical presentation, and response to treatment that vary on a patient-to-patient basis. Such variability creates a need to identify characteristics within patient popu...

Mining features for biomedical data using clustering tree ensembles.

Journal of biomedical informatics
The volume of biomedical data available to the machine learning community grows very rapidly. A rational question is how informative these data really are or how discriminant the features describing the data instances are. Several biomedical datasets...

A hierarchical semi-supervised extreme learning machine method for EEG recognition.

Medical & biological engineering & computing
Feature extraction and classification is a vital part in motor imagery-based brain-computer interface (BCI) system. Traditional deep learning (DL) methods usually perform better with more labeled training samples. Unfortunately, the labeled samples a...

PROSES: A Web Server for Sequence-Based Protein Encoding.

Journal of computational biology : a journal of computational molecular cell biology
Recently, the number of the amino acid sequences shared in online databases is growing rapidly in huge amounts. By using sequence-derived features, machine learning algorithms are successfully applied to prediction of protein functional classes, prot...

Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution.

Journal of computational biology : a journal of computational molecular cell biology
Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impa...

Predicting Infectious Disease Using Deep Learning and Big Data.

International journal of environmental research and public health
Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individual and macro scales. The Korea Center for Disease Control (KCDC) operates a surveillance system to mi...

An End-to-End System for Automatic Urinary Particle Recognition with Convolutional Neural Network.

Journal of medical systems
The urine sediment analysis of particles in microscopic images can assist physicians in evaluating patients with renal and urinary tract diseases. Manual urine sediment examination is labor-intensive, subjective and time-consuming, and the traditiona...