AIMC Topic: Neoplasm Staging

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Establishment and clinical application value of an automatic diagnosis platform for rectal cancer T-staging based on a deep neural network.

Chinese medical journal
BACKGROUND: Colorectal cancer is harmful to the patient's life. The treatment of patients is determined by accurate preoperative staging. Magnetic resonance imaging (MRI) played an important role in the preoperative examination of patients with recta...

Prediction of Recurrence in Patients with Stage III Colon Cancer Using Conventional Clinicopathological Factors and Peripheral Blood Test Data: A New Analysis with Artificial Intelligence.

Oncology
BACKGROUND: Survival rate may be predicted by tumor-node-metastasis staging systems in colon cancer. In clinical practice, about 20 to 30 clinicopathological factors and blood test data have been used. Various predictive factors for recurrence have b...

A Staging Auxiliary Diagnosis Model for Nonsmall Cell Lung Cancer Based on the Intelligent Medical System.

Computational and mathematical methods in medicine
At present, human health is threatened by many diseases, and lung cancer is one of the most dangerous tumors that threaten human life. In most developing countries, due to the large population and lack of medical resources, it is difficult for doctor...

Radiomics to better characterize small renal masses.

World journal of urology
PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools to extract objective information from standard images to combine with clinical data, with the aim of improving diagnostic, prognostic, and predictive ...

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

Cancer immunology research
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...

LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.

Cancer research and treatment
PURPOSE: The role of tumor-infiltrating lymphocytes (TILs) in predicting lymph node metastasis (LNM) in patients with T1 colorectal cancer (CRC) remains unclear. Furthermore, clinical utility of a machine learning-based approach has not been widely s...

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

International journal of cancer
Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRLM) to surgery or conservative therapy. However, there is no well-recognized method for predicting pa...

Comparing Laparotomy with Robot-assisted Interval Debulking Surgery for Patients with Advanced Epithelial Ovarian Cancer Receiving Neoadjuvant Chemotherapy.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: Compare survival of patients with advanced epithelial ovarian cancer (EOC) undergoing interval debulking surgery (IDS) with either robot-assisted (R-IDS) or open (O-IDS) approach. Second, we assessed the impact of adjuvant and neoadj...