{"type":"ScholarlyArticle","title":"On AI-Assisted Pneumoconiosis Detection from Chest X-rays","authors":[{"name":"Yasmeena Akhter","slug":"yasmeena-akhter","given":"Yasmeena","family":"Akhter","affiliation":"Indian Institute of Technology Jodhpur , India"},{"name":"Rishabh Ranjan","slug":"rishabh-ranjan","given":"Rishabh","family":"Ranjan","affiliation":"Indian Institute of Technology Jodhpur , India"},{"name":"Richa Singh","slug":"richa-singh","given":"Richa","family":"Singh","affiliation":"Indian Institute of Technology Jodhpur , India"},{"name":"Mayank Vatsa","slug":"mayank-vatsa","given":"Mayank","family":"Vatsa","affiliation":"Indian Institute of Technology Jodhpur , India"},{"name":"Santanu Chaudhury","slug":"santanu-chaudhury","given":"Santanu","family":"Chaudhury","affiliation":"Indian Institute of Technology Jodhpur , India"}],"abstract":"According to theWorld Health Organization, Pneumoconiosis\r\naffects millions of workers globally,\r\nwith an estimated 260,000 deaths annually. The\r\nburden of Pneumoconiosis is particularly high in\r\nlow-income countries, where occupational safety\r\nstandards are often inadequate, and the prevalence\r\nof the disease is increasing rapidly. The reduced\r\navailability of expert medical care in rural areas,\r\nwhere these diseases are more prevalent, further\r\nadds to the delayed screening and unfavourable outcomes\r\nof the disease. This paper aims to highlight\r\nthe urgent need for early screening and detection\r\nof Pneumoconiosis, given its significant impact on\r\naffected individuals, their families, and societies as\r\na whole. With the help of low-cost machine learning\r\nmodels, early screening, detection, and prevention\r\nof Pneumoconiosis can help reduce healthcare\r\ncosts, particularly in low-income countries. In this\r\ndirection, this research focuses on designing AI solutions\r\nfor detecting different kinds of Pneumoconiosis\r\nfrom chest X-ray data. This will contribute\r\nto the Sustainable Development Goal 3 of ensuring\r\nhealthy lives and promoting well-being for all at all\r\nages, and present the framework for data collection\r\nand algorithm for detecting Pneumoconiosis\r\nfor early screening. The baseline results show that\r\nthe existing algorithms are unable to address this\r\nchallenge. Therefore, it is our assertion that this\r\nresearch will improve state-of-the-art algorithms of\r\nsegmentation, semantic segmentation, and classification\r\nnot only for this disease but in general medical\r\nimage analysis literature.","doi":"10.24963/ijcai.2023/705","url":"https://ijcai.org/proceedings/2023/705","pdf":"https://ijcai.org/proceedings/2023/0705.pdf","markdown":"https://ijcai.org/proceedings/2023/705.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/705","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"AI for Good - Projects","track":"AI for Good - Projects","number":705,"pages":{"first":6353,"last":6361},"keywords":["AI for Good - Projects: Machine Learning","AI for Good - Projects: Multidisciplinary Topics and Applications","AI for Good - Projects: Computer Vision","AI for Good - Projects: Humans and AI","AI for Good - Projects: AI Ethics, Trust, Fairness"],"videos":[],"references":[{"position":1,"raw":"[Akhter et al., 2023] Yasmeena Akhter, Richa Singh, and Mayank Vatsa. 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