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Artificial intelligence (AI), encompassing deep learning and machine learning (ML), has gained increasing prominence across various scientific disciplines. In this study, we utilized cervical cancer (CC) as a model to develop an AI-driven pipeline for the identification and validation of serum biomarkers for early cancer diagnosis, leveraging mass spectrometry-based proteomics data. By processing and normalizing serum polypeptide differential peaks from 240 patients, we employed eight distinct ML algorithms to classify and analyze these differential polypeptide peaks, subsequently constructing receiver operating characteristic (ROC) curves and confusion matrices. Key performance metrics, including accuracy, precision, recall, and F1 score, were systematically evaluated. Furthermore, by integrating feature importance values, Shapley values, and local interpretable model-agnostic explanation (LIME) values, we demonstrated that the diagnostic area under the curve (AUC) achieved by our multi-dimensional learning models approached 1, significantly outperforming the diagnostic AUC of single markers derived from the PRIDE database. These findings underscore the potential of proteomics-driven integrated machine learning as a robust strategy to enhance early cancer diagnosis, offering a promising avenue for clinical translation.<\/jats:p>","DOI":"10.3390\/bioengineering12030269","type":"journal-article","created":{"date-parts":[[2025,3,10]],"date-time":"2025-03-10T06:59:59Z","timestamp":1741589999000},"page":"269","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Integrated Machine Learning Algorithms-Enhanced Predication for Cervical Cancer from Mass Spectrometry-Based Proteomics Data"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0037-6828","authenticated-orcid":false,"given":"Da","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Oncology, The Second Affiliated Hospital, Xi\u2019an Jiaotong University, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0385-7689","authenticated-orcid":false,"given":"Lihong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Dermatology, The Second Affiliated Hospital, Xi\u2019an Jiaotong University, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8986-5470","authenticated-orcid":false,"given":"Bo","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2962-0818","authenticated-orcid":false,"given":"Aihong","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an 710000, China"},{"name":"Department of Clinical Research, Xianyang Hospital of Yan\u2019an University, Xianyang 712000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0060-4279","authenticated-orcid":false,"given":"Jiangbo","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an 710000, China"},{"name":"Department of Clinical Research, Xianyang Hospital of Yan\u2019an University, Xianyang 712000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongdong","family":"Tong","sequence":"additional","affiliation":[{"name":"Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4752-5236","authenticated-orcid":false,"given":"Bingju","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Cell Biology and Genetics, School of Basic Medical Sciences, Xi\u2019an Jiaotong University Health Science Center, Xi\u2019an 710000, China"},{"name":"Department of Clinical Research, Xianyang Hospital of Yan\u2019an University, Xianyang 712000, China"},{"name":"Department of Clinical Research, Rugao Hospital of Shenzhen Jingcheng Medical Group, Rugao 226500, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhangjian","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Oncology, The Second Affiliated Hospital, Xi\u2019an Jiaotong University, Xi\u2019an 710000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"229","DOI":"10.3322\/caac.21834","article-title":"Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"74","author":"Bray","year":"2024","journal-title":"CA Cancer J. 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