AIMC Topic: Machine Learning

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Learning the molecular grammar of protein condensates from sequence determinants and embeddings.

Proceedings of the National Academy of Sciences of the United States of America
Intracellular phase separation of proteins into biomolecular condensates is increasingly recognized as a process with a key role in cellular compartmentalization and regulation. Different hypotheses about the parameters that determine the tendency of...

Deep generative selection models of T and B cell receptor repertoires with soNNia.

Proceedings of the National Academy of Sciences of the United States of America
Subclasses of lymphocytes carry different functional roles to work together and produce an immune response and lasting immunity. Additionally to these functional roles, T and B cell lymphocytes rely on the diversity of their receptor chains to recogn...

A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

Physical therapy
OBJECTIVE: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of ...

Using deep learning for acoustic event classification: The case of natural disasters.

The Journal of the Acoustical Society of America
This study proposes a sound classification model for natural disasters. Deep learning techniques, a convolutional neural network (CNN) and long short-term memory (LSTM), were used to train two individual classifiers. The study was conducted using a d...

Machine learning in medicine: Medical droids, tricorders, and a computer named Hal 9000.

Nephrologie & therapeutique
The usage of artificial intelligence to evaluate histological images was recently explored in many different areas of pathology. Studies focusing on nephropathology demonstrated that algorithms could be trained to identify various structures of the k...

Artificial intelligence and metagenomics in intestinal diseases.

Journal of gastroenterology and hepatology
Gut microbiota has been shown to associate with the development of gastrointestinal diseases. In the last decade, development in whole metagenome sequencing and 16S rRNA sequencing technology has dramatically accelerated the gut microbiome's research...

Noninvasive early diagnosis of intestinal diseases based on artificial intelligence in genomics and microbiome.

Journal of gastroenterology and hepatology
The maturing development in artificial intelligence (AI) and genomics has propelled the advances in intestinal diseases including intestinal cancer, inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS). On the other hand, colorectal c...

Machine learning on microbiome research in gastrointestinal cancer.

Journal of gastroenterology and hepatology
Gastrointestinal cancer maintains the highest incidence and mortality rate among all cancers globally. In addition to genetic causes, it has been reported that individuals' diet and composition of the gastrointestinal microbiome have profound impacts...