Abstract
Rare or orphan diseases belong to one of the most severe groups of diseases. At the same time, early and accurate diagnosis of such diseases is a serious problem for general practitioners, pediatricians and therapists. The article discusses the possibilities of using machine learning methods, including artificial intelligence, to improve the diagnosis of rare diseases. Information is provided on various models developed by both international experts and Russian researchers.
Reference12 articles.
1. Segura-Bedmar I, Camino-Perdones D, Guerrero-Aspizua S. Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts. BMC Bioinformatics. 2022 Jul 6;23(1):263. doi: 10.1186/s12859-022-04810-y. PMID: 35794528; PMCID: PMC9258216.
2. «Takeda» i «Farmimeks» budut razvivat' diagnostiku redkikh zabolevanii v Rossii. PHARMPROM. Internet-resurs. https://pharmprom.ru/take-da-i-farmimeks-budut-razvivat-diagnostiku-red-kix-zabolevanij-v-rossii/?ysclid=lf5p34sow569226820. (Rezhim dostupa: 02.09.2023)
3. Miroshnichenko I.I., Val'dman E.A., Kuz'min I.I. Novoe prednaznachenie starykh lekarstv (obzor). Razrabotka i registratsiya lekarstvennykh sredstv. 2023;12(1):182-190. https://doi.org/10.33380/2305-2066-2023-12-1-182-190 [Miroshnichenko I.I., Valdman E.A., Kuz'min I.I. Old Drugs, New Indications (Review). Drug development & registration. 2023;12(1):182-190. (In Russ.)].
4. Jefferies JL, Spencer AK, Lau HA, Nelson MW, Giuliano JD, Zabinski JW, Boussios C, Curhan G, Gliklich RE, Warnock DG. A new approach to identifying patients with elevated risk for Fabry disease using a machine learning algorithm. Orphanet J Rare Dis. 2021 Dec 20;16(1):518. doi: 10.1186/s13023-021-02150-3. PMID: 34930374; PMCID: PMC8686369.
5. Hersh WR, Cohen AM, Nguyen MM, Bensching KL, Deloughery TG. Clinical study applying machine learning to detect a rare disease: results and lessons learned. JAMIA Open. 2022 Jun 30;5(2):ooac053. doi: 10.1093/jamiaopen/ooac053. PMID: 35783073; PMCID: PMC9243401.