AIMC Topic: Rare Diseases
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RareNet: a deep learning model for rare cancer diagnosis.
Scientific reports
Jul 2, 2025
Although significant advances have been made in the early detection of many cancers, challenges remain in the early diagnosis of rare cancers, including Wilms tumor, Clear Cell Sarcoma of the Kidney, Neuroblastoma, Osteosarcoma, and Acute Myeloid Leu...
Improving a data mining based diagnostic support tool for rare diseases on the example of M. Fabry: Gender differences need to be taken into account.
PloS one
Jun 30, 2025
BACKGROUND: Rare diseases often present with a variety of clinical symptoms and therefore are challenging to diagnose. Fabry disease is an x-linked rare metabolic disorder. The severity of symptoms is usually different in men and women. Since therape...
Applying artificial intelligence to rare diseases: a literature review highlighting lessons from Fabry disease.
Orphanet journal of rare diseases
Apr 17, 2025
BACKGROUND: Use of artificial intelligence (AI) in rare diseases has grown rapidly in recent years. In this review we have outlined the most common machine-learning and deep-learning methods currently being used to classify and analyse large amounts ...
Designing Clinical Trials for Patients With Rare Cancers: Connecting the Zebras.
American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Apr 14, 2025
The field of rare cancer research is rapidly transforming, marked by significant progress in clinical trials and treatment strategies. Rare cancers, as defined by the National Cancer Institute, occur in fewer than 150 cases per million people each ye...
A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches.
Scientific reports
Feb 26, 2025
Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment....
An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets.
Scientific data
Feb 8, 2025
Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health ...
Ontology-based expansion of virtual gene panels to improve diagnostic efficiency for rare genetic diseases.
BMC medical informatics and decision making
Feb 5, 2025
BACKGROUND: Virtual Gene Panels (VGP) comprising disease-associated causal genes are utilized in the diagnosis of rare genetic diseases to evaluate candidate genes identified by whole-genome and whole-exome sequencing. VGPs generated by the PanelApp ...
Integrating Machine Learning-Based Approaches into the Design of ASO Therapies.
Genes
Feb 2, 2025
Rare diseases impose a significant burden on affected individuals, caregivers, and healthcare systems worldwide. Developing effective therapeutics for these small patient populations presents substantial challenges. Antisense oligonucleotides (ASOs) ...
Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection.
International journal of computer assisted radiology and surgery
Dec 29, 2024
PURPOSE: This study explores the use of deep generative models to create synthetic ultrasound images for the detection of hemarthrosis in hemophilia patients. Addressing the challenge of sparse datasets in rare disease diagnostics, the study aims to ...
Hypothesis generation for rare and undiagnosed diseases through clustering and classifying time-versioned biological ontologies.
PloS one
Dec 26, 2024
Rare diseases affect 1-in-10 people in the United States and despite increased genetic testing, up to half never receive a diagnosis. Even when using advanced genome sequencing platforms to discover variants, if there is no connection between the var...
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