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Neoplasm Staging

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Deep learning for elective neck delineation: More consistent and time efficient.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND/PURPOSE: Delineation of the lymph node levels of the neck for irradiation of the elective clinical target volume in head and neck cancer (HNC) patients is time consuming and prone to interobserver variability (IOV), although international ...

Artificial intelligence quantified tumour-stroma ratio is an independent predictor for overall survival in resectable colorectal cancer.

EBioMedicine
BACKGROUND: An artificial intelligence method could accelerate the clinical implementation of tumour-stroma ratio (TSR), which has prognostic relevance in colorectal cancer (CRC). We, therefore, developed a deep learning model for the fully automated...

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning.

Gut
OBJECTIVE: Tumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic i...

Artificial Intelligence System to Determine Risk of T1 Colorectal Cancer Metastasis to Lymph Node.

Gastroenterology
BACKGROUND & AIMS: In accordance with guidelines, most patients with T1 colorectal cancers (CRC) undergo surgical resection with lymph node dissection, despite the low incidence (∼10%) of metastasis to lymph nodes. To reduce unnecessary surgical rese...