Solomou, Christodoulos and Kazakov, Dimitar Lubomirov orcid.org/0000-0002-0637-8106 (2021) Utilizing Chest X-rays for Age Prediction and Gender Classification. In: Proceedings of the 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI). INTERNATIONAL SEMINAR ON RESEARCH OF INFORMATION TECHNOLOGY AND INTELLIGENT SYSTEMS, 16-17 Dec 2021 IEEE , IDN
Abstract
In this paper we present a framework for automatically predicting the gender and age of a patient using chest x-rays (CXRs). The work of this paper derives from common situations in medical imaging where the gender/age of a patient might be missing or in situations where the x-ray is of poor quality, thus leaving the medical practitioner unable to treat the patient appropriately. The proposed framework comprises of training a large CNN which jointly outputs the gender/age of a CXR. For feature extraction, transfer learning was employed using the EfficientNetB0 architecture, with a custom trainable top layer for both classification and prediction. This framework was applied to a combination of publicly available data, which collectively represent a heterogeneous dataset showing a variation in terms of race, location, patient's health, and quality of image. Our results are robust with respect to these factors, as none of them was used as input to improve the results. In conclusion, Deep Learning can be implemented in the medical imaging domain for automatically predicting characteristics of a patient.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © IEEE, 2021. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details |
Keywords: | x-rays |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 09 Feb 2022 09:50 |
Last Modified: | 16 Oct 2024 11:16 |
Status: | Published |
Publisher: | IEEE |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:183419 |
Download
Filename: UtilizingChestX_raysforAgePredictionandGenderClassification.pdf
Description: UtilizingChestX-raysforAgePredictionandGenderClassification