AIMC Topic: Neoplasm Staging
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CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy.
BMC cancer
Mar 8, 2021
BACKGROUND: It is very important to accurately delineate the CTV on the patient's three-dimensional CT image in the radiotherapy process. Limited to the scarcity of clinical samples and the difficulty of automatic delineation, the research of automat...
Adequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma.
Frontiers in endocrinology
Mar 3, 2021
BACKGROUND: IBM's Watson for Oncology (WFO) is an artificial intelligence tool that trains by acquiring data from the Memorial Sloan Kettering Cancer Center and learns from test cases and experts. This study aimed to analyze the adequacy and effectiv...
Establishment and clinical application value of an automatic diagnosis platform for rectal cancer T-staging based on a deep neural network.
Chinese medical journal
Feb 25, 2021
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
Feb 24, 2021
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
Feb 8, 2021
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
Jan 26, 2021
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
Jan 11, 2021
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...
Machine Learning
Prognosis
Retrospective Studies
Female
Risk Factors
Humans
Immune Checkpoint Proteins
Venous Thrombosis
Neoplasm Invasiveness
Liver
Neoplasm Staging
Middle Aged
Hepatectomy
Risk Assessment
Young Adult
Portal Vein
Adolescent
Adult
Liver Neoplasms
Lymphocyte Count
T-Lymphocytes
Carcinoma, Hepatocellular
Kaplan-Meier Estimate
Male
Models, Immunological
LASSO-Based Machine Learning Algorithm for Prediction of Lymph Node Metastasis in T1 Colorectal Cancer.
Cancer research and treatment
Dec 29, 2020
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
Dec 29, 2020
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...
Development and Validation of a Machine Learning Model to Explore Tyrosine Kinase Inhibitor Response in Patients With Stage IV EGFR Variant-Positive Non-Small Cell Lung Cancer.
JAMA network open
Dec 1, 2020
IMPORTANCE: An end-to-end efficacy evaluation approach for identifying progression risk after epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitor (TKI) therapy in patients with stage IV EGFR variant-positive non-small cell lung cancer (...
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