AIMC Topic: Neoplasm Staging

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Machine Learning-Based Computational Models Derived From Large-Scale Radiographic-Radiomic Images Can Help Predict Adverse Histopathological Status of Gastric Cancer.

Clinical and translational gastroenterology Oct 1, 2019
INTRODUCTION: Adverse histopathological status (AHS) decreases outcomes of gastric cancer (GC). With the lack of a single factor with great reliability to preoperatively predict AHS, we developed a computational approach by integrating large-scale im...
Stomach Neoplasms Male Middle Aged Prevalence Image Processing, Computer-Assisted Prognosis Retrospective Studies Humans Tomography, X-Ray Computed Machine Learning Female Computer Simulation Reproducibility of Results Follow-Up Studies Contrast Media Neoplasm Invasiveness Neoplasm Staging Neoplasm Recurrence, Local Gastrectomy Disease-Free Survival Preoperative Period Kaplan-Meier Estimate Stomach
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Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non-Small-Cell Lung Cancer.

JCO clinical cancer informatics Sep 1, 2019
PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medicine and the design of clinical trials. We developed and validated machine-learning models for three important clinical end points in patients with adva...
Models, Biological Combined Modality Therapy Tumor Burden Neoplasm Metastasis Molecular Targeted Therapy Lung Neoplasms Kaplan-Meier Estimate Humans Treatment Outcome Stochastic Processes Carcinoma, Non-Small-Cell Lung Machine Learning Randomized Controlled Trials as Topic Algorithms Neoplasm Staging Prognosis
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Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool.
Decision Support Systems, Clinical Guideline Adherence Neoplasm Staging Medical Oncology Practice Guidelines as Topic Practice Patterns, Physicians' Oncologists Reproducibility of Results Breast Neoplasms Biomarkers, Tumor Cross-Sectional Studies Clinical Competence Humans Artificial Intelligence Clinical Decision-Making Female
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Obtaining Knowledge in Pathology Reports Through a Natural Language Processing Approach With Classification, Named-Entity Recognition, and Relation-Extraction Heuristics.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: Robust institutional tumor banks depend on continuous sample curation or else subsequent biopsy or resection specimens are overlooked after initial enrollment. Curation automation is hindered by semistructured free-text clinical pathology no...
Aged, 80 and over Young Adult Adult Male Middle Aged Algorithms Electronic Health Records Female Aged Workflow Heuristics Research Report Medical Informatics Pathology, Molecular Neoplasms Adolescent User-Computer Interface Natural Language Processing Neoplasm Staging Humans Machine Learning Software
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Automating the Capture of Structured Pathology Data for Prostate Cancer Clinical Care and Research.

JCO clinical cancer informatics Jul 1, 2019
PURPOSE: Cancer pathology findings are critical for many aspects of care but are often locked away as unstructured free text. Our objective was to develop a natural language processing (NLP) system to extract prostate pathology details from postopera...
Male User-Computer Interface Decision Support Systems, Clinical Natural Language Processing Prostatic Neoplasms Humans Neoplasm Staging Software Neoplasm Grading Algorithms Patient Care Reproducibility of Results Workflow Biomedical Research Medical Informatics
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[Clinical Application of Artificial Intelligence Recognition Technology 
in the Diagnosis of Stage T1 Lung Cancer].

Zhongguo fei ai za zhi = Chinese journal of lung cancer May 20, 2019
BACKGROUND: Lung cancer is the cancer with the highest morbidity and mortality at home and abroad at present. Using computed tomography (CT) to screen lung cancer nodules is a huge workload. To test the effect of artificial intelligence in automatic ...
Lung Neoplasms Neoplasm Staging Medical Informatics Humans Artificial Intelligence
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Exploring the survival prognosis of lung adenocarcinoma based on the cancer genome atlas database using artificial neural network.

Medicine May 1, 2019
The aim of this study was to investigate the clinical factors affecting the survival prognosis of lung adenocarcinoma, and to establish a predictive model of survival prognosis of lung adenocarcinoma by artificial neural network.Download the cancer g...
Aged, 80 and over Adult Male Middle Aged ROC Curve Lung Neoplasms Logistic Models Regression Analysis Predictive Value of Tests Neoplasm Staging Neural Networks, Computer Prognosis Female Risk Factors Aged Humans Cigarette Smoking Kaplan-Meier Estimate Adenocarcinoma of Lung Genomic Library
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A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic.

JCO clinical cancer informatics Apr 1, 2019
PURPOSE: Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model ...
Computational Biology Apoptosis Reproducibility of Results Humans Decision Trees Colorectal Neoplasms Machine Learning Biomarkers, Tumor Neoplasm Staging Algorithms Decision Support Systems, Clinical Models, Biological Prognosis
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Bone-Cancer Assessment and Destruction Pattern Analysis in Long-Bone X-ray Image.

Journal of digital imaging Apr 1, 2019
Bone cancer originates from bone and rapidly spreads to the rest of the body affecting the patient. A quick and preliminary diagnosis of bone cancer begins with the analysis of bone X-ray or MRI image. Compared to MRI, an X-ray image provides a low-c...
Neoplasm Grading Radiographic Image Interpretation, Computer-Assisted X-Rays Humans Support Vector Machine Magnetic Resonance Imaging Bone Neoplasms Neoplasm Staging
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Artificial intelligence system of faster region-based convolutional neural network surpassing senior radiologists in evaluation of metastatic lymph nodes of rectal cancer.

Chinese medical journal Feb 1, 2019
BACKGROUND: An artificial intelligence system of Faster Region-based Convolutional Neural Network (Faster R-CNN) is newly developed for the diagnosis of metastatic lymph node (LN) in rectal cancer patients. The primary objective of this study was to ...
Lymphatic Metastasis Neoplasm Staging Radiologists Rectal Neoplasms Aged Humans Neoplasm Recurrence, Local Aged, 80 and over Neural Networks, Computer Pathologists Artificial Intelligence Adult Female Male Middle Aged
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