AIMC Topic: Biopsy

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Predictive models with the use of omics and supervised machine learning to diagnose non-alcoholic fatty liver disease: A "non-invasive alternative" to liver biopsy?

Metabolism: clinical and experimental Nov 9, 2019
Supervised Machine Learning Non-alcoholic Fatty Liver Disease Humans Metabolomics Biopsy
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Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides.

JAMA network open Nov 1, 2019
IMPORTANCE: Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological patterns in high-resolution microscopy images have shown pro...
Humans Neural Networks, Computer Esophageal Neoplasms Microscopy Computer Simulation Datasets as Topic Deep Learning Barrett Esophagus Adenocarcinoma Biopsy
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Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 21, 2019
PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural netwo...
Area Under Curve Biopsy Neoplasm Recurrence, Local Survival Rate Male Middle Aged Disease Progression Deep Learning Image Processing, Computer-Assisted Staining and Labeling Follow-Up Studies Aged Aged, 80 and over Humans Young Adult Neural Networks, Computer Adult Algorithms Female Retrospective Studies Melanoma Risk Factors
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Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Radiology Oct 8, 2019
Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to provide diagnostic support for human interpretation requires further evaluation. Purpose To compare t...
Sensitivity and Specificity Male Middle Aged Humans Deep Learning Retrospective Studies Magnetic Resonance Imaging Aged Predictive Value of Tests Prostatic Neoplasms Biopsy
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Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions.

JAMA network open Oct 2, 2019
IMPORTANCE: A high proportion of suspicious pigmented skin lesions referred for investigation are benign. Techniques to improve the accuracy of melanoma diagnoses throughout the patient pathway are needed to reduce the pressure on secondary care and ...
Humans Prospective Studies Female Melanoma Male Middle Aged Deep Learning ROC Curve Skin Neoplasms Dermoscopy Aged Adult Photography Smartphone Area Under Curve Biopsy
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Deep Learning-Based Histopathologic Assessment of Kidney Tissue.

Journal of the American Society of Nephrology : JASN Sep 5, 2019
BACKGROUND: The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with perio...
Deep Learning Kidney Biopsy Humans Nephrectomy Kidney Transplantation
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Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.

European radiology Aug 29, 2019
OBJECTIVE: To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN).
Biopsy Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Humans Deep Learning Sensitivity and Specificity ROC Curve Male Area Under Curve Prostatic Neoplasms
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Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

European journal of cancer (Oxford, England : 1990) Aug 14, 2019
BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer s...
Male Surveys and Questionnaires Diagnosis, Differential Biopsy Skin Neoplasms Neural Networks, Computer Dermoscopy Humans Algorithms Sensitivity and Specificity Dermatologists Female Hospitals, University Melanoma Nevus
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Deep neural networks are superior to dermatologists in melanoma image classification.

European journal of cancer (Oxford, England : 1990) Aug 8, 2019
BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level preci...
Image Interpretation, Computer-Assisted Nevus Neural Networks, Computer Algorithms ROC Curve Melanoma Biopsy Skin Neoplasms Skin Humans Dermatologists Dermoscopy Reproducibility of Results Surveys and Questionnaires
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Assessment of Machine Learning of Breast Pathology Structures for Automated Differentiation of Breast Cancer and High-Risk Proliferative Lesions.

JAMA network open Aug 2, 2019
IMPORTANCE: Following recent US Food and Drug Administration approval, adoption of whole slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly among challenging breast biopsy specimens, may benefit from computerize...
Humans Neural Networks, Computer Machine Learning Female Sensitivity and Specificity Breast Neoplasms Reference Standards Carcinoma, Ductal Biopsy Registries Carcinoma, Intraductal, Noninfiltrating
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