AIMC Topic: Carcinoma

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Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer.

Scientific reports Aug 21, 2020
Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC...
Humans Machine Learning Prognosis Female Breast Neoplasms Carcinoma Datasets as Topic Receptors, Estrogen Recurrence Neoplasms, Hormone-Dependent Biomarkers, Tumor Logistic Models Sequence Analysis, RNA Estrogens
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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...
Carcinoma Clinical Studies as Topic Neoplasm Metastasis Proportional Hazards Models Machine Learning Colorectal Neoplasms Antineoplastic Agents Humans
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Deep learning for fully automated tumor segmentation and extraction of magnetic resonance radiomics features in cervical cancer.

European radiology Nov 11, 2019
OBJECTIVE: To develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics feature...
Humans Retrospective Studies Female Deep Learning Image Processing, Computer-Assisted Carcinoma Young Adult Tumor Burden Adult Uterine Cervical Neoplasms Diffusion Magnetic Resonance Imaging Middle Aged Carcinoma, Squamous Cell Reproducibility of Results Aged Aged, 80 and over
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Skin cancer diagnosis based on optimized convolutional neural network.

Artificial intelligence in medicine Nov 8, 2019
Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image pro...
Databases, Factual Computer Simulation Melanoma Skin Neoplasms Animals Humans Neural Networks, Computer Algorithms Predatory Behavior Whales Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Carcinoma Early Diagnosis
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Machine learning-based texture analysis for differentiation of large adrenal cortical tumours on CT.

Clinical radiology Jul 27, 2019
AIM: To compare the efficacy of computed tomography (CT) texture analysis and conventional evaluation by radiologists for differentiation between large adrenal adenomas and carcinomas.
Carcinoma Tomography, X-Ray Computed Female Aged Adult Contrast Media Adenoma Adrenal Gland Neoplasms Male Middle Aged Humans Machine Learning Retrospective Studies
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Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy.

Gastrointestinal endoscopy Nov 16, 2018
BACKGROUND AND AIMS: According to guidelines, endoscopic resection should only be performed for patients whose early gastric cancer invasion depth is within the mucosa or submucosa of the stomach regardless of lymph node involvement. The accurate pre...
Serous Membrane Gastrectomy Gastroscopy Female Gastric Mucosa Stomach Neoplasms Endoscopic Mucosal Resection Sensitivity and Specificity Male Image Processing, Computer-Assisted Diagnosis, Computer-Assisted Neoplasm Invasiveness Humans Carcinoma ROC Curve Neural Networks, Computer Artificial Intelligence
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Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
Databases, Factual Reproducibility of Results Sensitivity and Specificity Lung Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Carcinoma Image Processing, Computer-Assisted Lung Neoplasms Humans Neural Networks, Computer Algorithms Radiographic Image Enhancement Medical Errors Probability Pattern Recognition, Automated False Positive Reactions X-Rays
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Detecting oropharyngeal carcinoma using multispectral, narrow-band imaging and machine learning.

The Laryngoscope Mar 25, 2018
OBJECTIVE: To determine if multispectral narrow-band imaging (mNBI) can be used for automated, quantitative detection of oropharyngeal carcinoma (OPC).
Humans Narrow Band Imaging Aged, 80 and over Bayes Theorem Machine Learning Sensitivity and Specificity Male Carcinoma Prospective Studies Middle Aged Pattern Recognition, Automated Female Diagnosis, Differential Oropharyngeal Neoplasms Aged
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Differentiation of the Follicular Neoplasm on the Gray-Scale US by Image Selection Subsampling along with the Marginal Outline Using Convolutional Neural Network.

BioMed research international Dec 19, 2017
We conducted differentiations between thyroid follicular adenoma and carcinoma for 8-bit bitmap ultrasonography (US) images utilizing a deep-learning approach. For the data sets, we gathered small-boxed selected images adjacent to the marginal outlin...
Thyroid Nodule Carcinoma Humans Neural Networks, Computer Thyroid Neoplasms Ultrasonography
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Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma.

Cancer letters Jun 10, 2017
We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled 110 patients with advanced NPC. A total of 970 radiomic features were ex...
Treatment Failure Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Carcinoma Reproducibility of Results High-Throughput Screening Assays Risk Factors Humans Image Interpretation, Computer-Assisted ROC Curve Magnetic Resonance Imaging Risk Assessment Decision Support Techniques Linear Models Predictive Value of Tests Support Vector Machine Diagnosis, Computer-Assisted Area Under Curve
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