AIMC Topic: Unsupervised Machine Learning

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Muscle magnetic resonance characterization of STIM1 tubular aggregate myopathy using unsupervised learning.

PloS one
PURPOSE: Congenital myopathies are a heterogeneous group of diseases affecting the skeletal muscles and characterized by high clinical, genetic, and histological variability. Magnetic Resonance (MR) is a valuable tool for the assessment of involved m...

A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges.

Sensors (Basel, Switzerland)
Recently, various sophisticated methods, including machine learning and artificial intelligence, have been employed to examine health-related data. Medical professionals are acquiring enhanced diagnostic and treatment abilities by utilizing machine l...

Foundation models for generalist medical artificial intelligence.

Nature
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI) models is likely to usher in newfound capabilities in medicine. We propose a new paradigm for medical AI, which we refer to as generalist medical AI (GMAI)....

Mine local homogeneous representation by interaction information clustering with unsupervised learning in histopathology images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The success of data-driven deep learning for histopathology images often depends on high-quality training sets and fine-grained annotations. However, as tumors are heterogeneous and annotations are expensive, unsupervised le...

Decoding reappraisal and suppression from neural circuits: A combined supervised and unsupervised machine learning approach.

Cognitive, affective & behavioral neuroscience
Emotion regulation is a core construct of mental health and deficits in emotion regulation abilities lead to psychological disorders. Reappraisal and suppression are two widely studied emotion regulation strategies but, possibly due to methodological...

Spatial gradient consistency for unsupervised learning of hyperspectral demosaicking: application to surgical imaging.

International journal of computer assisted radiology and surgery
PURPOSE: Hyperspectral imaging has the potential to improve intraoperative decision making if tissue characterisation is performed in real-time and with high-resolution. Hyperspectral snapshot mosaic sensors offer a promising approach due to their fa...

An Unsupervised Machine Learning Approach to Evaluating the Association of Symptom Clusters With Adverse Outcomes Among Older Adults With Advanced Cancer: A Secondary Analysis of a Randomized Clinical Trial.

JAMA network open
IMPORTANCE: Older adults with advanced cancer who have high pretreatment symptom severity often experience adverse events during cancer treatments. Unsupervised machine learning may help stratify patients into different risk groups.

Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods.

Scientific reports
Genetic architecture of plasma lipidome provides insights into regulation of lipid metabolism and related diseases. We applied an unsupervised machine learning method, PGMRA, to discover phenotype-genotype many-to-many relations between genotype and ...

Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement ...

Alternative additives associated in the feeding of laying hens: performance, biometrics, bone traits, and economic evaluation-an unsupervised machine learning approach.

Tropical animal health and production
Given the current bans on the use of some growth promoting antibiotics in poultry nutrition, the need to use alternative additives which could replace traditional promoters in diets has arisen. The objective of this study was to evaluate the effect o...