AIMC Topic: Biomarkers

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Tox-GAN: An Artificial Intelligence Approach Alternative to Animal Studies-A Case Study With Toxicogenomics.

Toxicological sciences : an official journal of the Society of Toxicology
Animal studies are a critical component in biomedical research, pharmaceutical product development, and regulatory submissions. There is a worldwide effort in toxicology toward "reducing, refining, and replacing" animal use. Here, we proposed a deep ...

How to remove or control confounds in predictive models, with applications to brain biomarkers.

GigaScience
BACKGROUND: With increasing data sizes and more easily available computational methods, neurosciences rely more and more on predictive modeling with machine learning, e.g., to extract disease biomarkers. Yet, a successful prediction may capture a con...

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis.

The Pediatric infectious disease journal
BACKGROUND: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk f...

Parameter tuning in machine learning based on radiomics biomarkers of lung cancer.

Journal of X-ray science and technology
BACKGROUND: Lung cancer is one of the most common cancers, and early diagnosis and intervention can improve cancer cure rate.

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.

Gut microbes
The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this stu...

A Machine Learning-Based Holistic Approach to Predict the Clinical Course of Patients within the Alzheimer's Disease Spectrum.

Journal of Alzheimer's disease : JAD
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transitional condition between healthy aging and dementia. No reliable biomarkers are available to predict t...

A nine-hub-gene signature of metabolic syndrome identified using machine learning algorithms and integrated bioinformatics.

Bioengineered
Early risk assessments and interventions for metabolic syndrome (MetS) are limited because of a lack of effective biomarkers. In the present study, several candidate genes were selected as a blood-based transcriptomic signature for MetS. We collected...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Briefings in bioinformatics
Artificial intelligence, such as deep generative methods, represents a promising solution to de novo design of molecules with the desired properties. However, generating new molecules with biological activities toward two specific targets remains an ...