AIMC Topic: Machine Learning

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Application of machine learning in rheumatic disease research.

The Korean journal of internal medicine
Over the past decade, there has been a paradigm shift in how clinical data are collected, processed and utilized. Machine learning and artificial intelligence, fueled by breakthroughs in high-performance computing, data availability and algorithmic i...

Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning.

Journal of chemical information and modeling
Here we report PPB2 as a target prediction tool assigning targets to a query molecule based on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding composition (MQN), molecular shape and pharmacophores (Xfp), and subst...

CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features.

BMC medical genomics
BACKGROUND: Long noncoding RNAs (lncRNAs) are widely involved in the initiation and development of cancer. Although some computational methods have been proposed to identify cancer-related lncRNAs, there is still a demanding to improve the prediction...

PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.

BMC bioinformatics
BACKGROUND: Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-binding residue prediction approach...

Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques.

BMC bioinformatics
BACKGROUND: Cyclic peptide-based drug discovery is attracting increasing interest owing to its potential to avoid target protein depletion. In drug discovery, it is important to maintain the biostability of a drug within the proper range. Plasma prot...

Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs.

BMC bioinformatics
BACKGROUND: Distinction between pre-microRNAs (precursor microRNAs) and length-similar pseudo pre-microRNAs can reveal more about the regulatory mechanism of RNA biological processes. Machine learning techniques have been widely applied to deal with ...

Better medicine through machine learning: What's real, and what's artificial?

PLoS medicine
Machine Learning Special Issue Guest Editors Suchi Saria, Atul Butte, and Aziz Sheikh cut through the hyperbole with an accessible and accurate portrayal of the forefront of machine learning in clinical translation.

Prediction of fatty liver disease using machine learning algorithms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fatty liver disease (FLD) is a common clinical complication; it is associated with high morbidity and mortality. However, an early prediction of FLD patients provides an opportunity to make an appropriate strategy for preven...

Use of Machine Learning to Identify Follow-Up Recommendations in Radiology Reports.

Journal of the American College of Radiology : JACR
PURPOSE: The aims of this study were to assess follow-up recommendations in radiology reports, develop and assess traditional machine learning (TML) and deep learning (DL) models in identifying follow-up, and benchmark them against a natural language...

Machine learning for detecting moyamoya disease in plain skull radiography using a convolutional neural network.

EBioMedicine
BACKGROUND: Recently, innovative attempts have been made to identify moyamoya disease (MMD) by focusing on the morphological differences in the head of MMD patients. Following the recent revolution in the development of deep learning (DL) algorithms,...