AIMC Topic: Rare Diseases

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[Application and research progress of artificial intelligence in the diagnosis and treatment of rare lung diseases].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases Jan 12, 2026
Rare lung diseases are a group of diseases characterized by significant clinical heterogeneity, challenging diagnosis and treatment processes, and diverse underlying causes. Due to their uncommon symptoms and limited awareness among healthcare provid...
Artificial Intelligence Machine Learning Deep Learning Humans Cystic Fibrosis Hypertension, Pulmonary Rare Diseases Idiopathic Pulmonary Fibrosis Lung Diseases
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Accuracy of Large Language Models in Generating Rare Disease Differential Diagnosis Using Key Clinical Features.

Studies in health technology and informatics Aug 7, 2025
Generating differential diagnoses for rare disease patients can be time intensive and highly dependent on the background and training of the evaluating physicians. Large language models (LLMs) have the potential to complement this process by automati...
Humans Female Rare Diseases Large Language Models Diagnosis, Differential Natural Language Processing Male Diagnosis, Computer-Assisted
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Can Generative LLMs Help Classify Imbalanced Real-World Data? Exploring Rare Diseases on Social Media.

Studies in health technology and informatics Aug 7, 2025
Developmental and Epileptic Encephalopathies (DEEs) are rare, severe conditions often discussed by families on social media, offering valuable insights into their experiences. Identifying these messages amidst unrelated content is crucial but challen...
Rare Diseases Social Media Natural Language Processing Humans
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Digenic variant interpretation with hypothesis-driven explainable AI.

NAR genomics and bioinformatics Jun 1, 2025
The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing digenic combinations of variants based on the proband's phenotypes and f...
Genetic Variation Rare Diseases Humans Artificial Intelligence Phenotype Computational Biology Machine Learning
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Improving AI models for rare thyroid cancer subtype by text guided diffusion models.

Nature communications May 13, 2025
Artificial intelligence applications in oncology imaging often struggle with diagnosing rare tumors. We identify significant gaps in detecting uncommon thyroid cancer types with ultrasound, where scarce data leads to frequent misdiagnosis. Traditiona...
Humans Artificial Intelligence Rare Diseases Thyroid Neoplasms Ultrasonography
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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 Humans Rare Diseases 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).
Vocabulary, Controlled Rare Diseases Natural Language Processing Biological Ontologies Humans Phenotype
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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...
Artificial Intelligence Algorithms Prognosis Female Precision Medicine Humans Cluster Analysis Middle Aged Aged Neoplasms Rare Diseases Male Myelodysplastic Syndromes Deep Learning
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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.
Retinal Telangiectasis Humans Supervised Machine Learning Retrospective Studies Rare Diseases Female Middle Aged Male Deep Learning Tomography, Optical Coherence
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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...
Humans Amino Acid Metabolism, Inborn Errors Machine Learning Aromatic-L-Amino-Acid Decarboxylases Dopamine Natural Language Processing Rare Diseases
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