The role of digital pathology and artificial intelligence-assisted analysis in breast cancer diagnosis
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https://doi.org/10.5281/zenodo.14602751References
Misra A, Misra PK, Kumar H, Reddy TV, Ramamurthy S, Rao KG. Role of artificial intelligence in precision pathology of breast cancer. AIP Conference Proceedings, 2023;2603(1):020021.
Acs B, Rantalainen M, Hartman J. Artificial intelligence as the next step towards precision pathology. J Intern Med. 2020;288(1):62-81.
Smine Z, Poeta S, De Caluwé A, Desmet A, Garibaldi C, Brou Boni K, et al. Automated segmentation in planning-CT for breast cancer radiotherapy: A review of recent advances. Radiother Oncol. 2024;202:110615.
Golden JA. Deep Learning Algorithms for Detection of Lymph Node Metastases From Breast Cancer: Helping Artificial Intelligence Be Seen. JAMA. 2017;318(22):2184-6.
Niazi MKK, Parwani AV, Gurcan MN. Digital pathology and artificial intelligence. Lancet Oncol. 2019;20(5):e253-e261.
Tizhoosh HR, Pantanowitz L. Artificial Intelligence and Digital Pathology: Challenges and Opportunities. J Pathol Inform. 2018;9:38.
Dimitriou N, Arandjelović O, Caie PD. Deep Learning for Whole Slide Image Analysis: An Overview. Front Med (Lausanne). 2019;6:264.
Komura D, Ishikawa S. Machine Learning Methods for Histopathological Image Analysis. Comput Struct Biotechnol J. 2018;16:34-42.
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