AIMC Topic: Neoplasm Staging

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Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: A systematic review.

Oral oncology Jul 13, 2020
This systematic review analyses and describes the application and diagnostic accuracy of Artificial Intelligence (AI) methods used for detection and grading of potentially malignant (pre-cancerous) and cancerous head and neck lesions using whole slid...
Humans Artificial Intelligence Algorithms Disease Susceptibility Deep Learning Head and Neck Neoplasms Databases, Genetic Neoplasm Staging Neoplasm Grading Disease Management Precancerous Conditions
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Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology Jul 8, 2020
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...
Molecular Docking Simulation Gene Expression Profiling Cell Line, Tumor Gene Expression Regulation, Neoplastic Adenocarcinoma Humans Machine Learning Algorithms Prognosis Benzimidazoles Fatty Acid-Binding Proteins Gastrointestinal Hormones Epistasis, Genetic Aminopyridines Databases, Protein Drug Repositioning Neoplasm Staging Colonic Neoplasms Survival Analysis
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Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.

Cancer research and treatment Jun 30, 2020
PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of SLNs by a pathologist is not easy and is a tedious and...
Middle Aged Deep Learning ROC Curve Image Processing, Computer-Assisted Lymphatic Metastasis Predictive Value of Tests Humans Female Neoplasm Staging Republic of Korea Aged Sentinel Lymph Node Aged, 80 and over Sentinel Lymph Node Biopsy Adult Frozen Sections Breast Neoplasms
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Hypothesis-free deep survival learning applied to the tumour microenvironment in gastric cancer.

The journal of pathology. Clinical research Jun 27, 2020
The biological complexity reflected in histology images requires advanced approaches for unbiased prognostication. Machine learning and particularly deep learning methods are increasingly applied in the field of digital pathology. In this study, we p...
Ki-67 Antigen Tissue Array Analysis Antigens, Differentiation, Myelomonocytic CD8 Antigens Antigens, CD Risk Assessment Humans Neoplasm Staging Deep Learning Image Interpretation, Computer-Assisted Risk Factors Time Factors Immunohistochemistry Stomach Neoplasms Cell Proliferation Antigens, CD20 Tumor Microenvironment Predictive Value of Tests Biomarkers, Tumor
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A machine learning-based prognostic predictor for stage III colon cancer.

Scientific reports Jun 25, 2020
Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis ...
Humans Machine Learning Prognosis Female Risk Factors Aged Colonic Neoplasms Risk Assessment Disease-Free Survival Colon Image Interpretation, Computer-Assisted Aged, 80 and over Follow-Up Studies Colectomy Young Adult Neoplasm Staging Kaplan-Meier Estimate Adult Neoplasm Recurrence, Local Male Middle Aged
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Automatic T Staging Using Weakly Supervised Deep Learning for Nasopharyngeal Carcinoma on MR Images.

Journal of magnetic resonance imaging : JMRI Jun 24, 2020
BACKGROUND: Recent studies have shown that deep learning can help tumor staging automatically. However, automatic nasopharyngeal carcinoma (NPC) staging is difficult due to the lack of large and slice-level annotated datasets.
Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Humans Retrospective Studies Deep Learning Magnetic Resonance Imaging Neoplasm Staging
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Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology Jun 24, 2020
Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contain...
Humans Machine Learning Cytokines Middle Aged Peptides Prognosis ROC Curve Female Neoplasm Staging Melanoma Neoplasm Metastasis Biomarkers, Tumor Male
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Deep learning-based survival prediction for multiple cancer types using histopathology images.

PloS one Jun 17, 2020
Providing prognostic information at the time of cancer diagnosis has important implications for treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and clinical variables can provide useful prognostic ...
Deep Learning Adult Sex Factors Image Processing, Computer-Assisted Humans Male Age Factors Survival Analysis Prognosis Middle Aged Neoplasm Staging Datasets as Topic Female Risk Assessment Feasibility Studies Risk Factors Neoplasms
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Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

European radiology Jun 10, 2020
OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).
Fluorodeoxyglucose F18 Kaplan-Meier Estimate Positron Emission Tomography Computed Tomography Neoplasm Staging Mouth Neoplasms Disease-Free Survival Tumor Burden Adult Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Glycolysis Treatment Outcome Squamous Cell Carcinoma of Head and Neck Predictive Value of Tests Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Humans Algorithms
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An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BMC bioinformatics Jun 8, 2020
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and accounts for cancer-related deaths. Survival rates are very low when the tumor is discovered in the late-stage. Thus, developing an efficient s...
Humans Machine Learning Female Kidney Neoplasms Carcinoma, Renal Cell ROC Curve Logistic Models Area Under Curve Neoplasm Staging RNA
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