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Machine learning in major depression: From classification to treatment outcome prediction
Aims Major depression disorder (MDD) is the single greatest cause of disability and
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
Are innovation and new technologies in precision medicine paving a new era in patients centric care?
Healthcare is undergoing a transformation, and it is imperative to leverage new technologies
to generate new data and support the advent of precision medicine (PM). Recent scientific …
to generate new data and support the advent of precision medicine (PM). Recent scientific …
Correlation feature selection based improved-binary particle swarm optimization for gene selection and cancer classification
DNA microarray technology has emerged as a prospective tool for diagnosis of cancer and
its classification. It provides better insights of many genetic mutations occurring within a cell …
its classification. It provides better insights of many genetic mutations occurring within a cell …
Prediction and analysis of essential genes using the enrichments of gene ontology and KEGG pathways
Identifying essential genes in a given organism is important for research on their
fundamental roles in organism survival. Furthermore, if possible, uncovering the links …
fundamental roles in organism survival. Furthermore, if possible, uncovering the links …
Better prediction of functional effects for sequence variants
Elucidating the effects of naturally occurring genetic variation is one of the major challenges
for personalized health and personalized medicine. Here, we introduce SNAP2, a novel …
for personalized health and personalized medicine. Here, we introduce SNAP2, a novel …
Machine-learning algorithms to automate morphological and functional assessments in 2D echocardiography
Background: Machine-learning models may aid cardiac phenotypic recognition by using
features of cardiac tissue deformation. Objectives: This study investigated the diagnostic …
features of cardiac tissue deformation. Objectives: This study investigated the diagnostic …
Data-driven advice for applying machine learning to bioinformatics problems
As the bioinformatics field grows, it must keep pace not only with new data but with new
algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used …
algorithms. Here we contribute a thorough analysis of 13 state-of-the-art, commonly used …
An ensemble machine learning approach for prediction and optimization of modulus of elasticity of recycled aggregate concrete
This paper presents an ensemble machine learning (ML) model for prediction of modulus of
elasticity (MOE) of concrete formulated using recycled concrete aggregate (RCA), in relation …
elasticity (MOE) of concrete formulated using recycled concrete aggregate (RCA), in relation …
[HTML][HTML] iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC
Abstract N 6-methyladenine (6mA) is one kind of post-replication modification (PTM or
PTRM) occurring in a wide range of DNA sequences. Accurate identification of its sites will …
PTRM) occurring in a wide range of DNA sequences. Accurate identification of its sites will …
In Silico Prediction of Chemical Toxicity for Drug Design Using Machine Learning Methods and Structural Alerts
During drug development, safety is always the most important issue, including a variety of
toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial …
toxicities and adverse drug effects, which should be evaluated in preclinical and clinical trial …