AIMC Topic: Machine Learning

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Resolution-based distillation for efficient histology image classification.

Artificial intelligence in medicine
Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the computing pipeline. This paper proposes a novel deep learning-based method...

Association of Machine Learning-Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking ...

Computer-Aided Colon Polyp Detection on High Resolution Colonoscopy Using Transfer Learning Techniques.

Sensors (Basel, Switzerland)
Colonoscopies reduce the incidence of colorectal cancer through early recognition and resecting of the colon polyps. However, the colon polyp miss detection rate is as high as 26% in conventional colonoscopy. The search for methods to decrease the po...

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

Scientific reports
Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as possible and move from a one-size-fits-all approach to a precision cardiometabolic prevention strategy ...

Improving stock trading decisions based on pattern recognition using machine learning technology.

PloS one
PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of dail...

Fe-based superconducting transition temperature modeling by machine learning: A computer science method.

PloS one
Searching for new high temperature superconductors has long been a key research issue. Fe-based superconductors attract researchers' attention due to their high transition temperature, strong irreversibility field, and excellent crystallographic symm...

Discriminant Projection Shared Dictionary Learning for Classification of Tumors Using Gene Expression Data.

IEEE/ACM transactions on computational biology and bioinformatics
With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as accurately as possible. The development of DNA microarrays provides an opportunity to predict tumor classification. One strategy is to use gene expre...

Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory.

IEEE/ACM transactions on computational biology and bioinformatics
Reconstruction of time-varying gene regulatory networks underlying a time-series gene expression data is a fundamental challenge in the computational systems biology. The challenge increases multi-fold if the target networks need to be constructed fo...

Hybrid Machine Learning Models for Predicting Types of Human T-cell Lymphotropic Virus.

IEEE/ACM transactions on computational biology and bioinformatics
Life threatening diseases like adult T-cell leukemia, neurodegenerative diseases, and demyelinating diseases such as HTLV-1 based myelopathy/tropical spastic paraparesis (HAM/TSP), hypocalcaemia, and bone lesions are caused by a group of human retrov...

Anatomy and Physiology of Artificial Intelligence in PET Imaging.

PET clinics
Artificial intelligence (AI) has seen an explosion in interest within nuclear medicine. This interest is driven by the rapid progress and eye-catching achievements of machine learning algorithms. The growing foothold of AI in molecular imaging is exp...