AIMC Topic: Machine Learning

Clear Filters Showing 12361 to 12370 of 34417 articles

Real-Time Tissue Classification Using a Novel Optical Needle Probe for Biopsy.

Applied spectroscopy
Core needle biopsy is a part of the histopathological process, which is required for cancerous tissue examination. The most common method to guide the needle inside of the body is ultrasound screening, which in greater part is also the only guidance ...

Robust Federated Learning for Heterogeneous Model and Data.

International journal of neural systems
Data privacy and security is an essential challenge in medical clinical settings, where individual hospital has its own sensitive patients data. Due to recent advances in decentralized machine learning in Federated Learning (FL), each hospital has it...

Artificial intelligence and machine learning algorithms in the detection of heavy metals in water and wastewater: Methodological and ethical challenges.

Chemosphere
Heavy metals (HMs) enter waterbodies through various means, which, when exceeding a threshold limit, cause toxic effects both on the environment and in humans upon entering their systems. Recent times have seen an increase in such HM influx incident ...

Application of machine learning-based read-across structure-property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye-sensitized solar cells (DSSCs).

Molecular informatics
The application of various in-silico-based approaches for the prediction of various properties of materials has been an effective alternative to experimental methods. Recently, the concepts of Quantitative structure-property relationship (QSPR) and r...

Adapting Deep Learning QSPR Models to Specific Drug Discovery Projects.

Molecular pharmaceutics
Medicinal chemistry and drug design efforts can be assisted by machine learning (ML) models that relate the molecular structure to compound properties. Such quantitative structure-property relationship models are generally trained on large data sets ...

Multimodal CNN-DDI: using multimodal CNN for drug to drug interaction associated events.

Scientific reports
Drug-to-drug interaction (DDIs) occurs when a patient consumes multiple drugs. Therefore, it is possible that any medication can influence other drugs' effectiveness. The drug-to-drug interactions are detected based on the interactions of chemical su...

Combined substituent number utilized machine learning for the development of antimicrobial agent.

Scientific reports
The utilization of machine learning has a potential to improve the environment of the development of antimicrobial agents. For practical use of machine learning, it is important that the conversion of molecules information to an appropriate descripto...

Timing matters for accurate identification of the epileptogenic zone.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Interictal biomarkers of the epileptogenic zone (EZ) and their use in machine learning models open promising avenues for improvement of epilepsy surgery evaluation. Currently, most studies restrict their analysis to short segments of intra...

Machine Learning Method and Hyperspectral Imaging for Precise Determination of Glucose and Silicon Levels.

Sensors (Basel, Switzerland)
This article introduces an algorithm for detecting glucose and silicon levels in solution. The research focuses on addressing the critical need for accurate and efficient glucose monitoring, particularly in the context of diabetic management. Underst...

Machine Learning Empowering Drug Discovery: Applications, Opportunities and Challenges.

Molecules (Basel, Switzerland)
Drug discovery plays a critical role in advancing human health by developing new medications and treatments to combat diseases. How to accelerate the pace and reduce the costs of new drug discovery has long been a key concern for the pharmaceutical i...