AIMC Topic: Machine Learning

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Recall Network: A Simple Brain-Inspired Algorithm for Classification.

Computational intelligence and neuroscience
The latest development of neuroscience has deepened the understanding of the information-processing mechanisms in the human brain and inspired a couple of sophisticated computational methods, such as deep learning, memory networks, and hierarchical t...

Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

Scientific reports
Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target...

Biosensors and machine learning for enhanced detection, stratification, and classification of cells: a review.

Biomedical microdevices
Biological cells, by definition, are the basic units which contain the fundamental molecules of life of which all living things are composed. Understanding how they function and differentiating cells from one another, therefore, is of paramount impor...

Pneumonia Detection in Chest X-Ray Images Using Enhanced Restricted Boltzmann Machine.

Journal of healthcare engineering
The process of pneumonia detection has been the focus of researchers as it has proved itself to be one of the most dangerous and life-threatening disorders. In recent years, many machine learning and deep learning algorithms have been applied in an a...

A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction.

Disease markers
The deep learning methods for various disease prediction tasks have become very effective and even surpass human experts. However, the lack of interpretability and medical expertise limits its clinical application. This paper combines knowledge repre...

Machine learning applications in upper gastrointestinal cancer surgery: a systematic review.

Surgical endoscopy
BACKGROUND: Machine learning (ML) has seen an increase in application, and is an important element of a digital evolution. The role of ML within upper gastrointestinal surgery for malignancies has not been evaluated properly in the literature. Theref...

Self-supervised learning in medicine and healthcare.

Nature biomedical engineering
The development of medical applications of machine learning has required manual annotation of data, often by medical experts. Yet, the availability of large-scale unannotated data provides opportunities for the development of better machine-learning ...

Nested epistasis enhancer networks for robust genome regulation.

Science (New York, N.Y.)
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...