Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?

Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?

Publication date: Nov 27, 2019

The amount of data collected and managed in (bio)medicine is ever-increasing. Thus, there is a need to rapidly and efficiently collect, analyze, and characterize all this information. Artificial intelligence (AI), with an emphasis on deep learning, holds great promise in this area and is already being successfully applied to basic research, diagnosis, drug discovery, and clinical trials. Rare diseases (RDs), which are severely underrepresented in basic and clinical research, can particularly benefit from AI technologies. Of the more than 7000 RDs described worldwide, only 5% have a treatment. The ability of AI technologies to integrate and analyze data from different sources (e.g., multi-omics, patient registries, and so on) can be used to overcome RDs’ challenges (e.g., low diagnostic rates, reduced number of patients, geographical dispersion, and so on). Ultimately, RDs’ AI-mediated knowledge could significantly boost therapy development. Presently, there are AI approaches being used in RDs and this review aims to collect and summarize these advances. A section dedicated to congenital disorders of glycosylation (CDG), a particular group of orphan RDs that can serve as a potential study model for other common diseases and RDs, has also been included.

Brasil, S., Pascoal, C., Francisco, R., Ferreira, Dos Reis., Videira, P.A., and Valad~ao, A.G. Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter? 05870. 2019 Genes (Basel) (10):12.

Concepts Keywords
AI Dedicated congenital disorders
Artificial Intelligence Big congenital disorders
Basel Chemistry
Biomedicine Physical sciences
Clinical Trials Natural sciences
Congenital Disorders Biochemistry
Deep Learning Carbohydrates
Dispersion Posttranslational modification
Drug Discovery Rare disease
Glycosylation Artificial intelligence
Omics CDG
RDs Drug discovery
Artificial intelligence


Type Source Name
disease MESH Rare Diseases
disease MESH diagnosis
disease MESH multi
disease MESH development
disease MESH congenital disorders of glycosylation
drug DRUGBANK Methyl 4 6-O-[(1r)-1-Carboxyethylidene]-Beta-D-Galactopyranoside


Original Article

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