AIMC Topic: Rare Diseases
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An Enhanced Classification Framework for Limited IoHT Time Series Data Using Ensemble Deep Learning and Image Encoding.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
Recent studies have illuminated the potential of harnessing the power of Deep Learning (DL) and the Internet of Health Things (IoHT) to detect a variety of disorders, particularly among patients in the middle to later stages of the disease. The utili...
KG-Hub-building and exchanging biological knowledge graphs.
Bioinformatics (Oxford, England)
Jul 1, 2023
MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is...
Context-Sensitive Common Data Models for Genetic Rare Diseases - A Concept.
Studies in health technology and informatics
Jun 29, 2023
Current challenges of rare diseases need to involve patients, physicians, and the research community to generate new insights on comprehensive patient cohorts. Interestingly, the integration of patient context has been insufficiently considered, but ...
Artificial Intelligence in the Genetic Diagnosis of Rare Disease.
Clinics in laboratory medicine
Mar 1, 2023
POPDx: an automated framework for patient phenotyping across 392 246 individuals in the UK Biobank study.
Journal of the American Medical Informatics Association : JAMIA
Jan 18, 2023
OBJECTIVE: For the UK Biobank, standardized phenotype codes are associated with patients who have been hospitalized but are missing for many patients who have been treated exclusively in an outpatient setting. We describe a method for phenotype recog...
Natural History and Real-World Data in Rare Diseases: Applications, Limitations, and Future Perspectives.
Journal of clinical pharmacology
Dec 1, 2022
Rare diseases represent a highly heterogeneous group of disorders with high phenotypic and genotypic diversity within individual conditions. Due to the small numbers of people affected, there are unique challenges in understanding rare diseases and d...
Conception, Development and Validation of Classification Methods for Coding Support of Rare Diseases Using Artificial Intelligence.
Studies in health technology and informatics
Jun 29, 2022
Automated coding of diseases can support hospitals in the billing of inpatient cases with the health insurance funds. This paper describes the implementation and evaluation of classification methods for two selected Rare Diseases. Different classifie...
Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome.
Studies in health technology and informatics
May 25, 2022
The wide adoption of Electronic Health Records (EHR) in hospitals provides unique opportunities for high throughput phenotyping of patients. The phenotype extraction from narrative reports can be performed by using either dictionary-based or data-dri...
Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.
PET clinics
Jan 1, 2022
Almost 1 in 10 individuals can suffer from one of many rare diseases (RDs). The average time to diagnosis for an RD patient is as high as 7 years. Artificial intelligence (AI)-based positron emission tomography (PET), if implemented appropriately, ha...
Machine learning application for patient stratification and phenotype/genotype investigation in a rare disease.
Briefings in bioinformatics
Sep 2, 2021
Alkaptonuria (AKU, OMIM: 203500) is an autosomal recessive disorder caused by mutations in the Homogentisate 1,2-dioxygenase (HGD) gene. A lack of standardized data, information and methodologies to assess disease severity and progression represents ...
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