Artificial Intelligence in Rare Disease Diagnosis and Treatment

Overview

Journal Clin Transl Sci

Specialties Biomedical Engineering
General Medicine

Date 2023 Aug 30

PMID 37646577

Authors

Magda Wojtara

Emaan Rana

Taibia Rahman

Palak Khanna

Heshwin Singh

Affiliations

Soon will be listed here.

Abstract

Artificial intelligence (AI) utilization in health care has grown over the past few years. It also has demonstrated potential in improving the efficiency of diagnosis and treatment. Some types of AI, such as machine learning, allow for the efficient analysis of vast datasets, identifying patterns, and generating key insights. Predictions can then be made for medical diagnosis and personalized treatment recommendations. The use of AI can bypass some conventional limitations associated with rare diseases. Namely, it can optimize traditional randomized control trials, and may eventually reduce costs for drug research and development. Recent advancements have enabled researchers to train models based on large datasets and then fine-tune these models on smaller datasets typically associated with rare diseases. In this mini-review, we discuss recent advancements in AI and how AI can be applied to streamline rare disease diagnosis and optimize treatment.

Citing Articles

A bibliometric study of rare diseases in English and Chinese databases from 1985 to 2024 based on CiteSpace.

Tian M, Wang S, Meng Z, Zhang X, Han J, Lu Y Intractable Rare Dis Res. 2025; 14(1):14-28.

PMID: 40046028 PMC: 11878225. DOI: 10.5582/irdr.2024.01062.

A Comparison of Transfer Learning Metaphyseal Sign Diagnostic Models for Kashin-Beck Disease Based on X-rays of Children's Hands.

Li G, Zhang H, Chen P, Song Y, Zhang Y, Li C Cureus. 2025; 17(1):e78235.

PMID: 40027020 PMC: 11871940. DOI: 10.7759/cureus.78235.

Quantifying hope: an EU perspective of rare disease therapeutic space and market dynamics.

Cacoub E, Lefebvre N, Milunov D, Sarkar M, Saha S Front Public Health. 2025; 13:1520467.

PMID: 39963479 PMC: 11830808. DOI: 10.3389/fpubh.2025.1520467.

Evaluation of the Performance of Three Large Language Models in Clinical Decision Support: A Comparative Study Based on Actual Cases.

Wang X, Ye H, Zhang S, Yang M, Wang X J Med Syst. 2025; 49(1):23.

PMID: 39948214 DOI: 10.1007/s10916-025-02152-9.

Telemedicine for Personalized Nutritional Intervention of Rare Diseases: A Narrative Review on Approaches, Impact, and Future Perspectives.

Eletti F, Tagi V, Greco I, Stucchi E, Fiore G, Bonaventura E Nutrients. 2025; 17(3).

PMID: 39940313 PMC: 11820740. DOI: 10.3390/nu17030455.

References

Liu J, Barrett J, Leonardi E, Lee L, Roychoudhury S, Chen Y . Natural History and Real-World Data in Rare Diseases: Applications, Limitations, and Future Perspectives. J Clin Pharmacol. 2022; 62 Suppl 2:S38-S55. PMC: 10107901. DOI: 10.1002/jcph.2134. View

Visibelli A, Roncaglia B, Spiga O, Santucci A . The Impact of Artificial Intelligence in the Odyssey of Rare Diseases. Biomedicines. 2023; 11(3). PMC: 10045927. DOI: 10.3390/biomedicines11030887. View

Brasil S, Neves C, Rijoff T, Falcao M, Valadao G, Videira P . Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases. Front Mol Biosci. 2021; 8:648012. PMC: 8131862. DOI: 10.3389/fmolb.2021.648012. View

Petzold A, Albrecht P, Balcer L, Bekkers E, Brandt A, Calabresi P . Artificial intelligence extension of the OSCAR-IB criteria. Ann Clin Transl Neurol. 2021; 8(7):1528-1542. PMC: 8283174. DOI: 10.1002/acn3.51320. View

Taroni J, Grayson P, Hu Q, Eddy S, Kretzler M, Merkel P . MultiPLIER: A Transfer Learning Framework for Transcriptomics Reveals Systemic Features of Rare Disease. Cell Syst. 2019; 8(5):380-394.e4. PMC: 6538307. DOI: 10.1016/j.cels.2019.04.003. View

Ardahan Sevgili S, Senol S . Prediction of chemotherapy-related complications in pediatric oncology patients: artificial intelligence and machine learning implementations. Pediatr Res. 2022; 93(2):390-395. DOI: 10.1038/s41390-022-02356-6. View

Alves V, Korn D, Pervitsky V, Thieme A, Capuzzi S, Baker N . Knowledge-based approaches to drug discovery for rare diseases. Drug Discov Today. 2021; 27(2):490-502. PMC: 9124594. DOI: 10.1016/j.drudis.2021.10.014. View

Bonomi F, Peretti S, Lepri G, Venerito V, Russo E, Bruni C . The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review. J Pers Med. 2022; 12(8). PMC: 9331823. DOI: 10.3390/jpm12081198. View

Faviez C, Chen X, Garcelon N, Neuraz A, Knebelmann B, Salomon R . Diagnosis support systems for rare diseases: a scoping review. Orphanet J Rare Dis. 2020; 15(1):94. PMC: 7164220. DOI: 10.1186/s13023-020-01374-z. View

10.

Krawitz P . [Artificial intelligence in the diagnosis of rare disorders: the development of phenotype analysis]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2022; 65(11):1159-1163. PMC: 9636278. DOI: 10.1007/s00103-022-03602-2. View

11.

Hurvitz N, Azmanov H, Kesler A, Ilan Y . Establishing a second-generation artificial intelligence-based system for improving diagnosis, treatment, and monitoring of patients with rare diseases. Eur J Hum Genet. 2021; 29(10):1485-1490. PMC: 8484657. DOI: 10.1038/s41431-021-00928-4. View

12.

Brasil S, Pascoal C, Francisco R, Dos Reis Ferreira V, Videira P, Valadao A . Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?. Genes (Basel). 2019; 10(12). PMC: 6947640. DOI: 10.3390/genes10120978. View

13.

Huang B, Huang H, Zhang S, Zhang D, Shi Q, Liu J . Artificial intelligence in pancreatic cancer. Theranostics. 2022; 12(16):6931-6954. PMC: 9576619. DOI: 10.7150/thno.77949. View

14.

James K, Phadke S, Wong T, Chowdhury S . Artificial Intelligence in the Genetic Diagnosis of Rare Disease. Clin Lab Med. 2023; 43(1):127-143. DOI: 10.1016/j.cll.2022.09.023. View

15.

Wojtara M, Rana E, Rahman T, Khanna P, Singh H . Artificial intelligence in rare disease diagnosis and treatment. Clin Transl Sci. 2023; 16(11):2106-2111. PMC: 10651639. DOI: 10.1111/cts.13619. View

16.

Alvarez-Machancoses O, Fernandez-Martinez J . Using artificial intelligence methods to speed up drug discovery. Expert Opin Drug Discov. 2019; 14(8):769-777. DOI: 10.1080/17460441.2019.1621284. View