AIMC Topic: Neoplasm Metastasis

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Convolutional Neural Networks in Predicting Nodal and Distant Metastatic Potential of Newly Diagnosed Non-Small Cell Lung Cancer on FDG PET Images.

AJR. American journal of roentgenology Apr 29, 2020
The purpose of this study was to assess, by analyzing features of the primary tumor with F-FDG PET, the utility of deep machine learning with a convolutional neural network (CNN) in predicting the potential of newly diagnosed non-small cell lung can...
Positron Emission Tomography Computed Tomography Radiopharmaceuticals Neoplasm Metastasis Fluorodeoxyglucose F18 Lung Neoplasms Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis Predictive Value of Tests Retrospective Studies Female Aged Aged, 80 and over Adult Humans Sensitivity and Specificity Neural Networks, Computer Male Middle Aged Imaging, Three-Dimensional
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Machine Learning Analysis of Individual Tumor Lesions in Four Metastatic Colorectal Cancer Clinical Studies: Linking Tumor Heterogeneity to Overall Survival.

The AAPS journal Mar 16, 2020
Total tumor size (TS) metrics used in TS models in oncology do not consider tumor heterogeneity, which could help to better predict drug efficacy. We analyzed individual target lesions (iTLs) of patients with metastatic colorectal carcinoma (mCRC) to...
Colorectal Neoplasms Antineoplastic Agents Carcinoma Clinical Studies as Topic Neoplasm Metastasis Humans Machine Learning Proportional Hazards Models
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Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning.

Scientific reports Mar 13, 2020
Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate prognostic stratification of NSCLC can become an important clinical reference when designing therapeutic strategies for cancer patients. With this clinical ...
Deep Learning Lung Neoplasms Computational Biology Support Vector Machine Carcinoma, Non-Small-Cell Lung Humans Reproducibility of Results Biomarkers, Tumor Neoplasm Metastasis Microarray Analysis Kaplan-Meier Estimate Area Under Curve Neoplasm Staging Neoplasm Grading Workflow
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A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns.

Nature communications Feb 5, 2020
In cancer, the primary tumour's organ of origin and histopathology are the strongest determinants of its clinical behaviour, but in 3% of cases a patient presents with a metastatic tumour and no obvious primary. Here, as part of the ICGC/TCGA Pan-Can...
Humans Computational Biology Mutation Whole Genome Sequencing Neoplasm Metastasis Genome, Human Female Reproducibility of Results Male Neoplasms Deep Learning
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Propofol affects the growth and metastasis of pancreatic cancer via ADAM8.

Pharmacological reports : PR Dec 20, 2019
BACKGROUND: Anesthesia is a major component of surgery and recently considered an important regulator of cell phenotypes. Here we aimed to investigate propofol, an anesthesia drug, in suppressing pancreatic cancer (PDAC), focusing on A disintegrin an...
Neoplasm Invasiveness Pancreatic Neoplasms Matrix Metalloproteinase 9 Xenograft Model Antitumor Assays Membrane Proteins Matrix Metalloproteinase 2 Neoplasm Metastasis Cell Proliferation Humans MAP Kinase Signaling System Propofol Animals ADAM Proteins Cell Movement Antineoplastic Agents Mice, SCID Apoptosis Cell Line, Tumor
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CT-based radiomics for prediction of histologic subtype and metastatic disease in primary malignant lung neoplasms.

International journal of computer assisted radiology and surgery Nov 13, 2019
PURPOSE: As some of the most important factors for treatment decision of lung cancer (which is the deadliest neoplasm) are staging and histology, this work aimed to associate quantitative contrast-enhanced computed tomography (CT) features from malig...
Biopsy Neoplasm Metastasis Aged, 80 and over Adult Male Middle Aged Lung ROC Curve Lung Neoplasms Predictive Value of Tests Neoplasm Staging Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Aged Humans
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An improved fuzzy-differential evolution approach applied to classification of tumors in liver CT scan images.

Medical & biological engineering & computing Aug 15, 2019
Fuzzy inference systems have been frequently used in medical diagnosis for managing uncertainty sources in the medical images. In addition, fuzzy systems have high level of interpretability because of using linguistic terms for knowledge representati...
Fuzzy Logic Area Under Curve Neoplasm Metastasis Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed ROC Curve Liver Neoplasms Image Processing, Computer-Assisted
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Prediction of early colorectal cancer metastasis by machine learning using digital slide images.

Computer methods and programs in biomedicine Jun 22, 2019
BACKGROUND AND OBJECTIVES: Prediction of lymph node metastasis (LNM) for early colorectal cancer (CRC) is critical for determining treatment strategies after endoscopic resection. Some histologic parameters for predicting LNM have been established, b...
Humans Machine Learning Algorithms Retrospective Studies Female Risk Factors Aged False Positive Reactions Keratins Lymph Nodes Lymphatic Metastasis Neoplasm Metastasis Immunohistochemistry False Negative Reactions Endoscopy Colorectal Neoplasms Male Middle Aged
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Deep transfer learning methods for colon cancer classification in confocal laser microscopy images.

International journal of computer assisted radiology and surgery May 25, 2019
PURPOSE: The gold standard for colorectal cancer metastases detection in the peritoneum is histological evaluation of a removed tissue sample. For feedback during interventions, real-time in vivo imaging with confocal laser microscopy has been propos...
Feasibility Studies Colonic Neoplasms Peritoneal Neoplasms Neoplasm Metastasis Humans Neural Networks, Computer Deep Learning Microscopy, Confocal
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Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment May 22, 2019
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.
Immunohistochemistry Kaplan-Meier Estimate Workflow Microscopy Survival Analysis Tumor Burden Image Processing, Computer-Assisted Neoplasm Metastasis Humans Follow-Up Studies Neoplasm Staging Neoplasm Grading Aged, 80 and over Adult Machine Learning Breast Neoplasms Prognosis Biomarkers, Tumor Female Middle Aged Aged
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