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4. Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal Cancers
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6. Benefits of Adjuvant Chemotherapy for Clinical T3-4N0 Rectal Cancer After Preoperative Chemoradiotherapy
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10. Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling
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12. Progress of MRI in predicting the circumferential resection margin of rectal cancer: A narrative review
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13. A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancer
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14. MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer
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16. Significance of MRI-based radiomics in predicting pathological complete response to neoadjuvant chemoradiotherapy of locally advanced rectal cancer: A narrative review
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17. Wavelets-Based Texture Analysis of Post Neoadjuvant Chemoradiotherapy Magnetic Resonance Imaging as a Tool for Recognition of Pathological Complete Response in Rectal Cancer, a Retrospective Study
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18. Combined transrectal ultrasound and radiomics model for evaluating the therapeutic effects of neoadjuvant chemoradiotherapy in locally advanced rectal cancer
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