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Rare Diseases

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Sensitive detection of rare disease-associated cell subsets via representation learning.

Nature communications Apr 6, 2017
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to de...
Rare Diseases Neoplasm, Residual Leukemia Immunologic Memory Survival Analysis Killer Cells, Natural T-Lymphocyte Subsets Cytomegalovirus Infections Supervised Machine Learning Cytokines Prognosis Single-Cell Analysis Monocytes Signal Transduction Acquired Immunodeficiency Syndrome Humans Neural Networks, Computer
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The Human Phenotype Ontology in 2017.

Nucleic acids research Nov 28, 2016
Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.hum...
Software Algorithms Phenotype Precision Medicine Genomics Genetic Association Studies Humans Rare Diseases Computational Biology Translational Research, Biomedical Biological Ontologies
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Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation.

Journal of biomedical semantics Mar 23, 2016
BACKGROUND: The Centre for Therapeutic Target Validation (CTTV - https://www.targetvalidation.org/) was established to generate therapeutic target evidence from genome-scale experiments and analyses. CTTV aims to support the validity of therapeutic t...
Molecular Targeted Therapy Rare Diseases Data Mining Biological Ontologies Databases, Factual Inflammatory Bowel Diseases Reproducibility of Results Humans Phenotype
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Integrating ontologies of rare diseases and radiological diagnosis.

Journal of the American Medical Informatics Association : JAMIA Mar 31, 2015
PURPOSE: The author sought to integrate an ontology of rare diseases with a large ontological model of radiological diagnosis.
Radiology Databases as Topic Biological Ontologies Humans Radiography Rare Diseases
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Disease Ontology 2015 update: an expanded and updated database of human diseases for linking biomedical knowledge through disease data.

Nucleic acids research Oct 27, 2014
The current version of the Human Disease Ontology (DO) (http://www.disease-ontology.org) database expands the utility of the ontology for the examination and comparison of genetic variation, phenotype, protein, drug and epitope data through the lens ...
Databases, Factual Internet Biological Ontologies Disease Rare Diseases Genetic Diseases, Inborn Humans
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MedBot vs RealDoc: efficacy of large language modeling in physician-patient communication for rare diseases.

Journal of the American Medical Informatics Association : JAMIA May 1, 2025
OBJECTIVES: This study assesses the abilities of 2 large language models (LLMs), GPT-4 and BioMistral 7B, in responding to patient queries, particularly concerning rare diseases, and compares their performance with that of physicians.
Physician-Patient Relations Rare Diseases Humans Communication
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Fine-tuning large language models for rare disease concept normalization.

Journal of the American Medical Informatics Association : JAMIA Sep 1, 2024
OBJECTIVE: We aim to develop a novel method for rare disease concept normalization by fine-tuning Llama 2, an open-source large language model (LLM), using a domain-specific corpus sourced from the Human Phenotype Ontology (HPO).
Biological Ontologies Vocabulary, Controlled Rare Diseases Humans Phenotype Natural Language Processing
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MOSAIC: An Artificial Intelligence-Based Framework for Multimodal Analysis, Classification, and Personalized Prognostic Assessment in Rare Cancers.

JCO clinical cancer informatics Jun 1, 2024
PURPOSE: Rare cancers constitute over 20% of human neoplasms, often affecting patients with unmet medical needs. The development of effective classification and prognostication systems is crucial to improve the decision-making process and drive innov...
Cluster Analysis Myelodysplastic Syndromes Rare Diseases Middle Aged Neoplasms Deep Learning Algorithms Precision Medicine Prognosis Female Aged Male Humans Artificial Intelligence
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Self-Supervised Learning for Improved Optical Coherence Tomography Detection of Macular Telangiectasia Type 2.

JAMA ophthalmology Mar 1, 2024
IMPORTANCE: Deep learning image analysis often depends on large, labeled datasets, which are difficult to obtain for rare diseases.
Humans Middle Aged Deep Learning Tomography, Optical Coherence Retrospective Studies Female Male Retinal Telangiectasis Supervised Machine Learning Rare Diseases
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Automatically pre-screening patients for the rare disease aromatic l-amino acid decarboxylase deficiency using knowledge engineering, natural language processing, and machine learning on a large EHR population.

Journal of the American Medical Informatics Association : JAMIA Feb 16, 2024
OBJECTIVES: Electronic health record (EHR) data may facilitate the identification of rare diseases in patients, such as aromatic l-amino acid decarboxylase deficiency (AADCd), an autosomal recessive disease caused by pathogenic variants in the dopa d...
Amino Acid Metabolism, Inborn Errors Aromatic-L-Amino-Acid Decarboxylases Natural Language Processing Dopamine Rare Diseases Humans Machine Learning
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