Deep learning based blood abnormalities detection as a tool for VEXAS syndrome screening

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De Almeida Braga, Cédric;Bauvais, Maxence;Sujobert, Pierre;Heiblig, Maël;Jullien, Maxime;Le Calvez, Baptiste;Richard, Camille;Le Roc' h, Valentin;Rault, Emmanuelle;Hérault, Olivier;Peterlin, Pierre;Garnier, Alice;Chevallier, Patrice;Bouzy, Simon;Le Bris, Yannick;Néel, Antoine;Graveleau, Julie;Kosmider, Olivier;Paul-Gilloteaux, Perrine;Normand, Nicolas;Eveillard, Marion

Description

Annotated image dataset from the paper :De Almeida Braga, C., Bauvais, M., Sujobert, P., Heiblig, M., Jullien, M., Le Calvez, B., Richard, C., Le Roc'h, V., Rault, E., Hérault, O., Peterlin, P., Garnier, A., Chevallier, P., Bouzy, S., Le Bris, Y., Néel, A., Graveleau, J., Kosmider, O., Paul-Gilloteaux, P., Normand, N. and Eveillard, M. (2024), Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening. Int J Lab Hematol. https://doi.org/10.1111/ijlh.14368Please refer to the paper for additionnal information on collection methods and findings related to the data.Please cite the paper if you use this data.The project contains .csv annotation files and image folders structured as follows :train/ centre_ID/ patient_ID/ slide_ID/ 000000.jpg 000001.jpg ...test/ centre_ID/ patient_ID/ slide_ID/ ...train.csvtest.csv

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

65%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Mendeley Data

License

Creative Commons Attribution Non Commercial 3.0 Unported

Assigned Domain

Subfield

Molecular Biology

Field

Biochemistry, Genetics and Molecular Biology

Domain

Life Sciences

Confidence Score

36%

Source

Scholar Data Model

Keywords

MicroscopyBiomedical ImagingImage Classification

Normalization Factors

FT

53.85

CTw

1.00

MTw

1.00