AIMC Topic: Rare Diseases

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[Artificial intelligence in the diagnosis of rare disorders: the development of phenotype analysis].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Rare diseases can often be diagnosed by carefully assessing the phenotype of the patient, as characteristic deviations (dysmorphisms) occur in many genetic diseases. These affect, for example, the features of the face - the "facial gestalt."This pape...

Deep learning for rare disease: A scoping review.

Journal of biomedical informatics
Although individually rare, collectively more than 7,000 rare diseases affect about 10% of patients. Each of the rare diseases impacts the quality of life for patients and their families, and incurs significant societal costs. The low prevalence of e...

OARD: Open annotations for rare diseases and their phenotypes based on real-world data.

American journal of human genetics
Diagnosis for rare genetic diseases often relies on phenotype-driven methods, which hinge on the accuracy and completeness of the rare disease phenotypes in the underlying annotation knowledgebase. Existing knowledgebases are often manually curated w...

Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts.

BMC bioinformatics
BACKGROUND AND OBJECTIVE: Although rare diseases are characterized by low prevalence, approximately 400 million people are affected by a rare disease. The early and accurate diagnosis of these conditions is a major challenge for general practitioners...

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.

Nature genetics
Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient pho...

Knowledge-based approaches to drug discovery for rare diseases.

Drug discovery today
The conventional drug discovery pipeline has proven to be unsustainable for rare diseases. Herein, we discuss recent advances in biomedical knowledge mining applied to discovering therapeutics for rare diseases. We summarize current chemogenomics dat...

The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems.

Orphanet journal of rare diseases
BACKGROUND: Rare diseases (RD) are a diverse collection of more than 7-10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorder...

Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases.

Genome medicine
BACKGROUND: Clinical interpretation of genetic variants in the context of the patient's phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds p...

A Survey of Autoencoder Algorithms to Pave the Diagnosis of Rare Diseases.

International journal of molecular sciences
Rare diseases (RDs) concern a broad range of disorders and can result from various origins. For a long time, the scientific community was unaware of RDs. Impressive progress has already been made for certain RDs; however, due to the lack of sufficien...