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The F1 value performance of CNN, MH-Net, GMDH, HCT-net and the new medical image diagnostic model proposed in this study was compared and analyzed in multiple iterations, aiming to evaluate the diagnostic performance of each model and verify the validity of the model proposed in this study. The experimental results show that the medical image diagnosis model proposed in this study shows a high F1 value under most iterations, indicating that the model has significant advantages in comprehensive evaluation accuracy and recall rate. The experiment also found that although GMDH and HCT-net models also have certain diagnostic capabilities, they have obvious limitations in processing complex medical image data, such as insufficient feature extraction or limited pattern recognition ability. The research will continue to optimize the structure and parameter Settings of the model proposed in this study, while exploring more advanced network structures and optimization algorithms to further improve its diagnostic performance.<\/jats:p>","DOI":"10.1142\/s0218126625504407","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T10:03:01Z","timestamp":1754560981000},"source":"Crossref","is-referenced-by-count":0,"title":["Medical Image Diagnosis Method Based on Hybrid Neural Network in Medical IoT Scenarios"],"prefix":"10.1142","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-8093-1546","authenticated-orcid":false,"given":"Qi","family":"Gao","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Baotou Medical College, Baotou 014040, Inner Mongolia, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-2221-597X","authenticated-orcid":false,"given":"Yuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Baotou Medical College, Baotou 014040, Inner Mongolia, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2025,10,17]]},"reference":[{"key":"S0218126625504407BIB001","first-page":"28","volume":"1","author":"G\u00fclg\u00fcn O. 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