{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T15:35:40Z","timestamp":1772724940603,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,24]]},"DOI":"10.1145\/3721201.3721368","type":"proceedings-article","created":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T13:35:21Z","timestamp":1762954521000},"page":"199-210","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Explainable Feature Engineering in Health Data Science: Empirical Comparison of ChatGPT-4o and Classical Machine Learning Methods"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3151-1885","authenticated-orcid":false,"given":"Behshid","family":"Behkamal","sequence":"first","affiliation":[{"name":"Western University, London, Ontario, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5281-9022","authenticated-orcid":false,"given":"Amin","family":"Rezaei","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2741-2981","authenticated-orcid":false,"given":"Nickolas","family":"Littlefield","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6997-4850","authenticated-orcid":false,"given":"Samarth","family":"Bhardwaj","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7431-7997","authenticated-orcid":false,"given":"Leah","family":"Reid","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5555-2005","authenticated-orcid":false,"given":"Nicole","family":"Myers","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7517-0739","authenticated-orcid":false,"given":"Soheyla","family":"Amirian","sequence":"additional","affiliation":[{"name":"Pace University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9650-2862","authenticated-orcid":false,"given":"Ahmad P.","family":"Tafti","sequence":"additional","affiliation":[{"name":"University of Pittsburgh, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,11,12]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"d.]. Surveillance, Epidemiology, and End Results (SEER) Program Research Data (1973\u20132013)","year":"2023","unstructured":"[n. d.]. Surveillance, Epidemiology, and End Results (SEER) Program Research Data (1973\u20132013), National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, released April 2023, based on the November 2022 submission. ([n. d.])."},{"key":"e_1_3_2_1_2_1","volume-title":"Principal component analysis","author":"Abdi Herv\u00e9","year":"2010","unstructured":"Herv\u00e9 Abdi and Lynne J Williams. 2010. Principal component analysis. Wiley interdisciplinary reviews: computational statistics 2, 4 (2010), 433\u2013459."},{"key":"e_1_3_2_1_3_1","first-page":"30","article-title":"Using machine learning for healthcare challenges and opportunities","volume":"1","author":"Alanazi A.","year":"2022","unstructured":"A. Alanazi. 2022. Using machine learning for healthcare challenges and opportunities. Informatics in Medicine Unlocked Jan 1 (2022), 30.","journal-title":"Informatics in Medicine Unlocked Jan"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.glmedi.2023.100026"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-023-01925-4"},{"key":"e_1_3_2_1_6_1","volume-title":"J\u00e9r\u00e9my Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, et al.","author":"Casper Stephen","year":"2023","unstructured":"Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, J\u00e9r\u00e9my Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, et al. 2023. Open problems and fundamental limitations of reinforcement learning from human feedback. arXiv preprint arXiv:2307.15217 (2023)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.2312.17117"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3114836"},{"key":"e_1_3_2_1_9_1","first-page":"1","article-title":"Palm: Scaling language modeling with pathways","volume":"24","author":"Chowdhery Aakanksha","year":"2023","unstructured":"Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023. Palm: Scaling language modeling with pathways. Journal of Machine Learning Research 24, 240 (2023), 1\u2013113.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_10_1","first-page":"1","article-title":"Scaling instruction-finetuned language models","volume":"25","author":"Chung Hyung Won","year":"2024","unstructured":"Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2024. Scaling instruction-finetuned language models. Journal of Machine Learning Research 25, 70 (2024), 1\u201353.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"R. Das and DJ. Wales. 2017. Machine learning landscapes and predictions for patient outcomes. Royal Society open science Jul 26 (2017) 4.","DOI":"10.1098\/rsos.170175"},{"key":"e_1_3_2_1_12_1","volume-title":"Cohortgpt: An enhanced gpt for participant recruitment in clinical study. arXiv preprint arXiv:2307.11346","author":"Guan Zihan","year":"2023","unstructured":"Zihan Guan, Zihao Wu, Zhengliang Liu, Dufan Wu, Hui Ren, Quanzheng Li, Xiang Li, and Ninghao Liu. 2023. Cohortgpt: An enhanced gpt for participant recruitment in clinical study. arXiv preprint arXiv:2307.11346 (2023)."},{"key":"e_1_3_2_1_13_1","unstructured":"Mark A Hall. 1999. Correlation-based feature selection for machine learning. Ph.D. Dissertation. The University of Waikato."},{"key":"e_1_3_2_1_14_1","volume-title":"Bressem","author":"Han Tianyu","year":"2023","unstructured":"Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, Paul Grundmann, Tom Oberhauser, Alexander L\u00f6ser, Daniel Truhn, and Keno K. Bressem. 2023. MedAlpaca - An Open-Source Collection of Medical Conversational AI Models and Training Data. arXiv:2304.08247 [cs.CL]"},{"key":"e_1_3_2_1_15_1","volume-title":"A review of feature selection methods with applications. In 2015 38th international convention on information and communication technology, electronics and microelectronics (MIPRO). Ieee, 1200\u20131205","author":"Jovi\u0107 Alan","unstructured":"Alan Jovi\u0107, Karla Brki\u0107, and Nikola Bogunovi\u0107. 2015. A review of feature selection methods with applications. In 2015 38th international convention on information and communication technology, electronics and microelectronics (MIPRO). Ieee, 1200\u20131205."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/70.1.163"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jksuci.2019.06.012"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICHI57859.2023.00131"},{"key":"e_1_3_2_1_19_1","volume-title":"Chat-GPT in healthcare: a taxonomy and systematic review. Computer Methods and Programs in Biomedicine","author":"Li Jianning","year":"2024","unstructured":"Jianning Li, Amin Dada, Behrus Puladi, Jens Kleesiek, and Jan Egger. 2024. Chat-GPT in healthcare: a taxonomy and systematic review. Computer Methods and Programs in Biomedicine (2024), 108013."},{"key":"e_1_3_2_1_20_1","volume-title":"ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge. Cureus 15, 6","author":"Li Yunxiang","year":"2023","unstructured":"Yunxiang Li, Zihan Li, Kai Zhang, Ruilong Dan, Steve Jiang, and You Zhang. 2023. ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge. Cureus 15, 6 (2023)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbac409"},{"key":"e_1_3_2_1_22_1","first-page":"2529","article-title":"Learning Feature Engineering for Classification","volume":"17","author":"Nargesian Fatemeh","year":"2017","unstructured":"Fatemeh Nargesian, Horst Samulowitz, Udayan Khurana, Elias B Khalil, and Deepak S Turaga. 2017. Learning Feature Engineering for Classification.. In Ijcai, Vol. 17. 2529\u20132535.","journal-title":"Ijcai"},{"key":"e_1_3_2_1_23_1","first-page":"2","article-title":"Analyzing the impact of feature selection on the accuracy of heart disease prediction","volume":"1","author":"Pathan M. S.","year":"2022","unstructured":"M. S. Pathan, A. Nag, M. M. Pathan, and S. Dev. 2022. Analyzing the impact of feature selection on the accuracy of heart disease prediction. Healthcare Analytics Nov 1 (2022), 2.","journal-title":"Healthcare Analytics Nov"},{"key":"e_1_3_2_1_24_1","volume-title":"InIntelligent Computing. In Proceedings of the 2019 Computing Conference","volume":"1","author":"Rado O.","unstructured":"O. Rado, N. Ali, H. M. Sani, A. Idris, and D. Neagu. 2019. Performance analysis of feature selection methods for classification of healthcare datasets. InIntelligent Computing. In Proceedings of the 2019 Computing Conference, Volume 1. International Publishing. Springer, 929\u2013938."},{"key":"e_1_3_2_1_25_1","volume-title":"Explainable trustworthy","author":"Rasheed K.","year":"2022","unstructured":"K. Rasheed, A. Qayyum, M. Ghaly, A. Al-Fuqaha, A. Razi, and Qadir J. Explainable trustworthy. 2022. and ethical machine learning for healthcare: A survey. Computers in Biology and Medicine Sep 7 (2022). Article 106043."},{"key":"e_1_3_2_1_26_1","volume-title":"Evaluating large language models for use in healthcare: A framework for translational value assessment. Informatics in Medicine Unlocked","author":"Reddy Sandeep","year":"2023","unstructured":"Sandeep Reddy. 2023. Evaluating large language models for use in healthcare: A framework for translational value assessment. Informatics in Medicine Unlocked (2023), 101304."},{"key":"e_1_3_2_1_27_1","volume-title":"A review of feature selection methods in medical applications. Computers in biology and medicine 112","author":"Remeseiro Beatriz","year":"2019","unstructured":"Beatriz Remeseiro and Veronica Bolon-Canedo. 2019. A review of feature selection methods in medical applications. Computers in biology and medicine 112 (2019), 103375."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"crossref","unstructured":"L. Rubinger A. Gazendam S. Ekhtiari and M. Bhandari. 2023. Machine learning and artificial intelligence in research and healthcare. Injury May 1 54 (2023) S69\u201373.","DOI":"10.1016\/j.injury.2022.01.046"},{"key":"e_1_3_2_1_29_1","volume-title":"Machine Learning Fairness and Explainability in Stage-Specific Cancer Survivability Prediction. In ECCB","author":"Kamble Tejasvi Sanjay","year":"2024","unstructured":"Tejasvi Sanjay Kamble, Hongtao Wang, Nicole Myers, Leah Reid, Cynthia S McCarthy, Young Ji Lee, Soheyla Amirian, Nickolas Littlefield, Hongfang Liu, Liron Pantanowitz, Hooman Rashidi, and AHmad P Tafti. 2024 (Under Review). Machine Learning Fairness and Explainability in Stage-Specific Cancer Survivability Prediction. In ECCB 2024. Oxford."},{"key":"e_1_3_2_1_30_1","volume-title":"In2011 3rd International Conference on Electronics Computer Technology 2011 Apr 8.","volume":"4","author":"Selvakuberan K.","unstructured":"K. Selvakuberan, D. Kayathiri, T. B. Harini, and MI. Devi. [n. d.]. An efficient feature selection method for classification in health care systems using machine learning techniques. In2011 3rd International Conference on Electronics Computer Technology 2011 Apr 8. Vol. 4,). IEEE ([n. d.]), 223\u2013226."},{"key":"e_1_3_2_1_31_1","volume-title":"Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al.","author":"Singhal Karan","year":"2023","unstructured":"Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al. 2023. Large language models encode clinical knowledge. Nature 620, 7972 (2023), 172\u2013180."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-023-04576-8"},{"key":"e_1_3_2_1_33_1","volume-title":"Medhalt: Medical domain hallucination test for large language models. arXiv preprint arXiv:2307.15343","author":"Umapathi Logesh Kumar","year":"2023","unstructured":"Logesh Kumar Umapathi, Ankit Pal, and Malaikannan Sankarasubbu. 2023. Medhalt: Medical domain hallucination test for large language models. arXiv preprint arXiv:2307.15343 (2023)."},{"key":"e_1_3_2_1_34_1","volume-title":"A review of feature selection and its methods. Cybernetics and information technologies 19, 1","author":"Venkatesh B","year":"2019","unstructured":"B Venkatesh and J Anuradha. 2019. A review of feature selection and its methods. Cybernetics and information technologies 19, 1 (2019), 3\u201326."},{"key":"e_1_3_2_1_35_1","volume-title":"[n. d.]. Explainable Machine Learning in Healthcare. InExplainable Machine Learning for Multimedia Based Healthcare Applications 2023 Sep 9","author":"Whig P.","unstructured":"P. Whig, S. Kouser, A. B. Bhatia, R. R. Nadikattu, and P. Sharma. [n. d.]. Explainable Machine Learning in Healthcare. InExplainable Machine Learning for Multimedia Based Healthcare Applications 2023 Sep 9. Springer International Publishing, Cham, 77\u201398."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"J. Wiens and ES. Shenoy. 2018. Machine learning for healthcare: on the verge of a major shift in healthcare epidemiology. Clinical infectious diseases Jan 1 66 (2018) 1.","DOI":"10.1093\/cid\/cix731"},{"key":"e_1_3_2_1_37_1","volume-title":"Harnessing the power of llms in practice: A survey on chatgpt and beyond. ACM Transactions on Knowledge Discovery from Data 18, 6","author":"Yang Jingfeng","year":"2024","unstructured":"Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Shaochen Zhong, Bing Yin, and Xia Hu. 2024. Harnessing the power of llms in practice: A survey on chatgpt and beyond. ACM Transactions on Knowledge Discovery from Data 18, 6 (2024), 1\u201332."},{"key":"e_1_3_2_1_38_1","volume-title":"Healthcare","volume":"11","author":"Yu Ping","year":"2023","unstructured":"Ping Yu, Hua Xu, Xia Hu, and Chao Deng. 2023. Leveraging generative AI and large Language models: a Comprehensive Roadmap for Healthcare Integration. In Healthcare, Vol. 11. MDPI, 2776."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.38094\/jastt1224"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.2310.00305"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1101\/2023.12.15.23300059"}],"event":{"name":"CHASE '25: ACM\/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies","location":"Yeshiva University Museum New York NY USA","acronym":"CHASE '25","sponsor":["SIGBED ACM Special Interest Group on Embedded Systems","IEEE Computer Society"]},"container-title":["Proceedings of the ACM\/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3721201.3721368","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T13:38:21Z","timestamp":1762954701000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3721201.3721368"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,24]]},"references-count":41,"alternative-id":["10.1145\/3721201.3721368","10.1145\/3721201"],"URL":"https:\/\/doi.org\/10.1145\/3721201.3721368","relation":{},"subject":[],"published":{"date-parts":[[2025,6,24]]},"assertion":[{"value":"2025-11-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}