A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches
Abstract Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world’s population. Most of them affect children, are chronic and progressive, and have no specific treatment. RD patients face diagnostic challenges,...
Saved in:
| Main Authors: | Matias Rolando, Victor Raggio, Hugo Naya, Lucia Spangenberg, Leticia Cagnina |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-90450-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
WCN24-864 Alport Syndrome: genetic variants, phenotypes of kidney disease and association with End Stage Kidney Disease in a Uruguayan Cohort
by: Federico Yandian, et al.
Published: (2024-04-01) -
Identification of a novel SACS gene mutation leading to spastic ataxia Charlevoix-Saguenay type: a case report
by: Víctor Raggio, et al.
Published: (2025-08-01) -
Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli
by: Dmitry Yu Isaev, et al.
Published: (2025-08-01) -
Survival analysis of patients with rare tumors of the uterine corpus – carcinosarcoma
by: Stevanović Nemanja, et al.
Published: (2024-01-01) -
EMCOR: a medical corpus for terminological purposes
by: Tamara Varela Vila, et al.
Published: (2012-07-01)