AIMC Topic: Autoimmune Diseases
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Machine learning application in autoimmune diseases: State of art and future prospectives.
Autoimmunity reviews
Dec 9, 2023
Autoimmune diseases are a group of disorders resulting from an alteration of immune tolerance, characterized by the formation of autoantibodies and the consequent development of heterogeneous clinical manifestations. Diagnosing autoimmune diseases is...
The Role of Artificial Intelligence in Deciphering Diet-Disease Relationships: Case Studies.
Annual review of nutrition
May 19, 2023
Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, i...
Modeling and insights into the structural characteristics of drug-induced autoimmune diseases.
Frontiers in immunology
Oct 24, 2022
The incidence and complexity of drug-induced autoimmune diseases (DIAD) have been on the rise in recent years, which may lead to serious or fatal consequences. Besides, many environmental and industrial chemicals can also cause DIAD. However, there a...
[Type 1 diabetes mellitus and Graves Basedow's disease, a case of Autoimmune Polyglandular Syndrome].
Andes pediatrica : revista Chilena de pediatria
Nov 5, 2021
INTRODUCTION: Type 1 diabetes mellitus (T1DM) is one of the most frequent autoimmune diseases in childhood. Its diagnosis requires the search for other autoimmune diseases.
A Classification Method for the Cellular Images Based on Active Learning and Cross-Modal Transfer Learning.
Sensors (Basel, Switzerland)
Feb 20, 2021
In computer-aided diagnosis (CAD) systems, the automatic classification of the different types of the human epithelial type 2 (HEp-2) cells represents one of the critical steps in the diagnosis procedure of autoimmune diseases. Most of the methods pr...
Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables.
Journal of child and adolescent psychopharmacology
May 28, 2020
Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder presenting with: unusually abrupt onset of obsessive compulsive disorder (OCD) or severe eating restrictions, with at least two concomitant cognitive, beha...
A Machine Learning Approach for High-Dimensional Time-to-Event Prediction With Application to Immunogenicity of Biotherapies in the ABIRISK Cohort.
Frontiers in immunology
Apr 7, 2020
Predicting immunogenicity for biotherapies using patient and drug-related factors represents nowadays a challenging issue. With the growing ability to collect massive amount of data, machine learning algorithms can provide efficient predictive tools....
Detecting mitotic cells in HEp-2 images as anomalies via one class classifier.
Computers in biology and medicine
Jun 17, 2019
We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided Diagnosis (CAD) system for Anti-Nuclear Antibodies (ANA) detection. In the proposed work, due to unique characteristics (the rare occurrence) of the ...
Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires.
Frontiers in immunology
Feb 21, 2018
The adaptive immune system recognizes antigens an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in...
Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.
Clinical lymphoma, myeloma & leukemia
Dec 2, 2017
BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell lymphoma (DLBCL). However, little is known about the demographics or clinical outcomes of DLBCL that...
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