AIMC Topic: Machine Learning

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Drug Intelligence Science (DISĀ®): Pioneering a high-resolution translational platform to enhance the probability of success for drug discovery and development.

Drug discovery today
Translational research has a crucial role in bridging the gap between basic biology discoveries and their clinical applications. Deep scientific understanding and advanced technology platforms are both crucial for translational research. Here, I desc...

Swarm Smart Meta-Estimator for 2D/2D Heterostructure Design.

Journal of chemical information and modeling
Two-dimensional (2D) semiconductors are central to many scientific fields. The combination of two semiconductors (heterostructure) is a good way to lift many technological deadlocks. Although ab initio calculations are useful to study physical proper...

Deciphering RNA splicing logic with interpretable machine learning.

Proceedings of the National Academy of Sciences of the United States of America
Machine learning methods, particularly neural networks trained on large datasets, are transforming how scientists approach scientific discovery and experimental design. However, current state-of-the-art neural networks are limited by their uninterpre...

Effects of MRI scanner manufacturers in classification tasks with deep learning models.

Scientific reports
Deep learning has become a leading subset of machine learning and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards m...

Dimensionality reduction for deep learning in infrared microscopy: a comparative computational survey.

The Analyst
While infrared microscopy provides molecular information at spatial resolution in a label-free manner, exploiting both spatial and molecular information for classifying the disease status of tissue samples constitutes a major challenge. One strategy ...

An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence.

IEEE journal of biomedical and health informatics
Difficulty in knowledge validation is a significant hindrance to knowledge discovery via data mining, especially automatic validation without artificial participation. In the field of medical research, medical knowledge discovery from electronic medi...

Federated Semi-Supervised Learning for Medical Image Segmentation via Pseudo-Label Denoising.

IEEE journal of biomedical and health informatics
Distributed big data and digital healthcare technologies have great potential to promote medical services, but challenges arise when it comes to learning predictive model from diverse and complex e-health datasets. Federated Learning (FL), as a colla...

Insight Extraction From E-Health Bookings by Means of Hypergraph and Machine Learning.

IEEE journal of biomedical and health informatics
New technologies are transforming medicine, and this revolution starts with data. Usually, health services within public healthcare systems are accessed through a booking centre managed by local health authorities and controlled by the regional gover...

Online Extra Trees Regressor.

IEEE transactions on neural networks and learning systems
Data production has followed an increased growth in the last years, to the point that traditional or batch machine-learning (ML) algorithms cannot cope with the sheer volume of generated data. Stream or online ML presents itself as a viable solution ...

A Review of Recurrent Neural Network-Based Methods in Computational Physiology.

IEEE transactions on neural networks and learning systems
Artificial intelligence and machine learning techniques have progressed dramatically and become powerful tools required to solve complicated tasks, such as computer vision, speech recognition, and natural language processing. Since these techniques h...