AI Medical Compendium Journal:
Journal of integrative bioinformatics

Showing 1 to 10 of 34 articles

Ion channel classification through machine learning and protein language model embeddings.

Journal of integrative bioinformatics
Ion channels are critical membrane proteins that regulate ion flux across cellular membranes, influencing numerous biological functions. The resource-intensive nature of traditional wet lab experiments for ion channel identification has led to an inc...

MCMVDRP: a multi-channel multi-view deep learning framework for cancer drug response prediction.

Journal of integrative bioinformatics
Drug therapy remains the primary approach to treating tumours. Variability among cancer patients, including variations in genomic profiles, often results in divergent therapeutic responses to analogous anti-cancer drug treatments within the same coho...

Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction.

Journal of integrative bioinformatics
This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental disorder with uncertain etiology. Deep Learning (DL) holds promise for analyzing large genomic datasets to uncover new risk factors. However, based o...

An overview of machine learning and deep learning techniques for predicting epileptic seizures.

Journal of integrative bioinformatics
Epilepsy is a neurological disorder (the third most common, following stroke and migraines). A key aspect of its diagnosis is the presence of seizures that occur without a known cause and the potential for new seizures to occur. Machine learning has ...

Application of Artificial Intelligence or machine learning in risk sharing agreements for pharmacotherapy risk management.

Journal of integrative bioinformatics
Applications of Artificial Intelligence in medical informatics solutions risk sharing have social value. At a time of ever-increasing cost for the provision of medicines to citizens, there is a need to restrain the growth of health care costs. The se...

Co-creation environment with cloud virtual reality and real-time artificial intelligence toward the design of molecular robots.

Journal of integrative bioinformatics
This paper describes the design philosophy for our cloud-based virtual reality (VR) co-creation environment (CCE) for molecular modeling. Using interactive VR simulation can provide enhanced perspectives in molecular modeling for intuitive live demon...

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare - a proof of concept study for the prediction of coronary artery calcification scores.

Journal of integrative bioinformatics
The implementation of Artificial Intelligence (AI) still faces significant hurdles and one key factor is the access to data. One approach that could support that is federated machine learning (FL) since it allows for privacy preserving data access. F...

KaIDA: a modular tool for assisting image annotation in deep learning.

Journal of integrative bioinformatics
Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehens...

Evaluating molecular representations in machine learning models for drug response prediction and interpretability.

Journal of integrative bioinformatics
Machine learning (ML) is increasingly being used to guide drug discovery processes. When applying ML approaches to chemical datasets, molecular descriptors and fingerprints are typically used to represent compounds as numerical vectors. However, in r...

Integrative analysis of chemical properties and functions of drugs for adverse drug reaction prediction based on multi-label deep neural network.

Journal of integrative bioinformatics
The prediction of adverse drug reactions (ADR) is an important step of drug discovery and design process. Different drug properties have been employed for ADR prediction but the prediction capability of drug properties and drug functions in integrate...