{"type":"ScholarlyArticle","title":"Data-Centric AI for Chest X-Ray Analysis in Resource-Constrained Settings","authors":[{"name":"Yasmeena Akhter","slug":"yasmeena-akhter","given":"Yasmeena","family":"Akhter","affiliation":""}],"abstract":"With approximately 2 billion chest X-ray examinations conducted globally each year, the demand for radiological interpretation far surpasses the available expertise, particularly in resource-constrained regions. Recent advancements in artificial intelligence and computer vision present promising solutions for automated chest X-ray analysis. Nevertheless, integrating AI-driven diagnostics into clinical practice encounters several challenges, including data-centric issues, implementation barriers, deployment complexities, and the need for trustworthy AI. This dissertation focuses on the data-centric aspect, making significant contributions through enhanced data collection, the creation of novel datasets, algorithm development, privacy-preserving collaborative learning, and modelling for low-resolution data. It offers practical methodologies for embedding AI into chest radiology workflows, with a particular emphasis on addressing underserved conditions and healthcare settings with limited data availability. Furthermore, this work illustrates how tailored AI solutions can democratize access to high-quality radiological care while balancing privacy considerations and operational constraints across diverse environments.","doi":"10.24963/ijcai.2025/1237","url":"https://ijcai.org/proceedings/2025/1237","pdf":"https://ijcai.org/proceedings/2025/1237.pdf","markdown":"https://ijcai.org/proceedings/2025/1237.md","bibtex":"https://ijcai.org/proceedings/2025/bibtex/1237","volume":{"slug":"2025","title":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2025","url":"https://ijcai.org/proceedings/2025/","year":2025,"location":"Montreal, Canada","dates":"16-22 August 2025","editors":"James Kwok","isbn":"978-1-956792-06-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2025"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":1237,"pages":{"first":10965,"last":10966},"keywords":["Computer Vision: CV: Transfer, low-shot, semi- and un- supervised learning","Multidisciplinary Topics and Applications: MDA: Computational sustainability","Computer Vision: CV: Machine learning for vision","Multidisciplinary Topics and Applications: MDA: Health and medicine","Machine Learning: ML: Applications","Machine Learning: ML: Attention models","Computer Vision: CV: Biomedical image analysis","Machine Learning: ML: Cost-sensitive learning","Machine Learning: ML: Classification","Machine Learning: ML: Ensemble methods","Computer Vision: CV: Applications","Machine Learning: ML: Multi-label","Machine Learning: ML: Convolutional networks","Computer Vision: CV: Representation learning","Machine Learning: ML: Representation learning","Machine Learning: ML: Multi-task and transfer learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}