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The diagnosis, prognosis, and the treatment of BC pose significant challenges that are responsible for their limited therapeutic efficacy. Omics\u2010based technologies have gained substantial attention in BC diagnosis through molecular profiling and diverse clinical analytics. The integration of metabolomics, proteomics, transcriptomics, and genomics provides a multidimensional approach to personalized BC diagnosis and treatment through high\u2010throughput molecular profiling. Moreover, the emergence of artificial intelligence (AI) has also supported more accurate and early diagnosis of BC through multimodal integration of diverse datasets. The integration of advanced deep learning (DL) and machine learning (ML) has been extensively exploited for tumor grading, histopathological classification, molecular profiling, diagnostic imaging, and prognostic prediction. This review aims to summarize recent developments in AI\u2010driven multi\u2010omics approaches for the discovery of BC biomarkers. We have also highlighted the integration of omics\u2010based data like metabolomics, proteomics, transcriptomics, and genomics with key AI techniques, including ML and DL, that play a crucial role in the inclusion of multi\u2010omics in cancer and biomarker discovery. We have further discussed AI\u2010based BC screening and diagnostic approaches, as well as the contribution of AI models for patient stratification, biomarker discovery, and prediction of therapeutic response. Additionally, key limitations and challenges, including data heterogeneity, high computational complexity, and model interpretability, have also been highlighted in the present review. Conclusively, we have also outlined future perspectives on the integration of AI and multi\u2010omics to revolutionize precision clinical medicine and improve clinical outcomes in BC theranostics.<\/jats:p>","DOI":"10.1002\/med.70078","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T10:39:49Z","timestamp":1784803189000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["AI\u2010Driven Multi\u2010Omics Integrated Applications Using Diverse Neural Networks for Breast Cancer Diagnostic Screening and Biomarker Discovery"],"prefix":"10.1002","author":[{"given":"Vandana","family":"Kumari","sequence":"first","affiliation":[{"name":"Centre of Experimental Medicine and Surgery, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harshita","family":"Tiwari","sequence":"additional","affiliation":[{"name":"Centre of Experimental Medicine and Surgery, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Swati","family":"Singh","sequence":"additional","affiliation":[{"name":"Centre of Experimental Medicine and Surgery, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vikas","family":"Kailashiya","sequence":"additional","affiliation":[{"name":"Department of Pathology, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nguyen Thi Thu","family":"Hoai","sequence":"additional","affiliation":[{"name":"Research Centre for Infectious Diseases (RCID) International University, Vietnam National University Ho Chi Minh City Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shikha","family":"Sachan","sequence":"additional","affiliation":[{"name":"Department of Obstetrics &amp; Gynaecology, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brijesh","family":"Kumar","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Indian Institute of Technology Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahul","family":"Kumar","sequence":"additional","affiliation":[{"name":"Department of Biotechnology Indian Institute of Technology Hyderabad, Kandi Sangareddy Telangana India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajiv","family":"Kumar","sequence":"additional","affiliation":[{"name":"Centre of Experimental Medicine and Surgery, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Navin Kumar","family":"Verma","sequence":"additional","affiliation":[{"name":"Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7956-9555","authenticated-orcid":false,"given":"Vibhav","family":"Gautam","sequence":"additional","affiliation":[{"name":"Centre of Experimental Medicine and Surgery, Institute of Medical Sciences Banaras Hindu University Varanasi Uttar Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"e_1_2_16_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40164-022-00363-1"},{"key":"e_1_2_16_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41572-019-0111-2"},{"key":"e_1_2_16_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers17071102"},{"key":"e_1_2_16_5_1","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1038\/s41598-018-37273-4","article-title":"Multi\u2010Omics Dataset to Decipher the Complexity of Drug Resistance in Diffuse Large B\u2010Cell Lymphoma","volume":"9","author":"Fornecker L.\u2010M.","year":"2019","journal-title":"Scientific Reports"},{"key":"e_1_2_16_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/molecules28124768"},{"key":"e_1_2_16_7_1","doi-asserted-by":"crossref","first-page":"423","DOI":"10.3389\/fonc.2020.00423","article-title":"Computational Oncology in the Multi\u2010Omics Era: State of the Art","volume":"10","author":"Anda\u2010J\u00e1uregui G.","year":"2020","journal-title":"Frontiers in Oncology"},{"key":"e_1_2_16_8_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0268967"},{"key":"e_1_2_16_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41568-022-00502-0"},{"key":"e_1_2_16_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105508"},{"key":"e_1_2_16_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13402-023-00912-8"},{"key":"e_1_2_16_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.breast.2017.09.003"},{"key":"e_1_2_16_13_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.ejrad.2025.112101","article-title":"AI\u2010Supported Approaches for Mammography Single and Double Reading: A Controlled Multireader Study","volume":"187","author":"Brancato B.","year":"2025","journal-title":"European Journal of Radiology"},{"key":"e_1_2_16_14_1","doi-asserted-by":"crossref","first-page":"3878","DOI":"10.3390\/cancers17233878","article-title":"Performance of an Artificial Intelligence Support System on Screening Mammography Cases Proceeding to Stereotactic Biopsy","volume":"17","author":"Mathur A.","year":"2025","journal-title":"Cancers"},{"key":"e_1_2_16_15_1","doi-asserted-by":"crossref","first-page":"115","DOI":"10.3390\/medicina62010115","article-title":"Contrast\u2010Enhanced Mammography and Deep Learning\u2010Derived Malignancy Scoring in Breast Cancer Molecular Subtype Assessment","volume":"62","author":"Feren\u010daba A. 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