AIMC Topic:
Image Interpretation, Computer-Assisted

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Artificial intelligence in digital breast pathology: Techniques and applications.

Breast (Edinburgh, Scotland) Dec 19, 2019
Breast cancer is the most common cancer and second leading cause of cancer-related death worldwide. The mainstay of breast cancer workup is histopathological diagnosis - which guides therapy and prognosis. However, emerging knowledge about the comple...
Breast Image Interpretation, Computer-Assisted Humans Female Artificial Intelligence Breast Neoplasms
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Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas.

AJNR. American journal of neuroradiology Dec 19, 2019
BACKGROUND AND PURPOSE: Patient survival in high-grade glioma remains poor, despite the recent developments in cancer treatment. As new chemo-, targeted molecular, and immune therapies emerge and show promising results in clinical trials, image-based...
Glioma Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Neuroimaging Middle Aged Deep Learning Cohort Studies Humans Prognosis Brain Neoplasms Male Retrospective Studies Female
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Enhanced Diagnosis of Severe Aortic Stenosis Using Artificial Intelligence: A Proof-of-Concept Study of 530,871 Echocardiograms.

JACC. Cardiovascular imaging Dec 18, 2019
Artificial Intelligence Databases, Factual Prognosis Aged, 80 and over Adult Female Aortic Valve Stenosis Aged Middle Aged Aortic Valve Severity of Illness Index Humans Predictive Value of Tests Hemodynamics Male Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Ventricular Function, Left Proof of Concept Study Echocardiography
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Use of Endoscopic Impression, Artificial Intelligence, and Pathologist Interpretation to Resolve Discrepancies Between Endoscopy and Pathology Analyses of Diminutive Colorectal Polyps.

Gastroenterology Dec 18, 2019
Optical Imaging Humans Adenoma Artificial Intelligence Colonic Polyps Decision Support Techniques Image Interpretation, Computer-Assisted Colorectal Neoplasms Colonoscopy
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CAD and AI for breast cancer-recent development and challenges.

The British journal of radiology Dec 16, 2019
Computer-aided diagnosis (CAD) has been a popular area of research and development in the past few decades. In CAD, machine learning methods and multidisciplinary knowledge and techniques are used to analyze the patient information and the results ca...
Breast Neoplasms Diagnosis, Computer-Assisted Deep Learning Decision Support Systems, Clinical Humans Neural Networks, Computer Artificial Intelligence Radiology Female Bibliometrics Ultrasonography, Mammary Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Quality Assurance, Health Care Mammography
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A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease.

NeuroImage Dec 16, 2019
Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can delay its progression, no effective cures are available for AD. Accura...
Humans Models, Theoretical Aged, 80 and over Magnetic Resonance Imaging Neuroimaging Sensitivity and Specificity Alzheimer Disease Neural Networks, Computer Male Image Interpretation, Computer-Assisted Female Cognitive Dysfunction Hippocampus Aged
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Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN).

Journal of medical systems Dec 14, 2019
Breast cancer is one of the leading causes of cancer death among women in worldwide. Early diagnosis of breast cancer improves the chance of survival by aiding proper clinical treatments. The digital mammography examination helps in diagnosing the br...
Breast Neoplasms Mammography Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Machine Learning
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An investigation of machine learning methods in delta-radiomics feature analysis.

PloS one Dec 13, 2019
PURPOSE: This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the...
Neoplasm Recurrence, Local ROC Curve Humans Image Interpretation, Computer-Assisted Glioma Machine Learning Radiosurgery Magnetic Resonance Imaging Algorithms
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Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence.

NeuroImage. Clinical Dec 9, 2019
The detection of new or enlarged white-matter lesions is a vital task in the monitoring of patients undergoing disease-modifying treatment for multiple sclerosis. However, the definition of 'new or enlarged' is not fixed, and it is known that lesion-...
Brain Adult Deep Learning Neuroimaging Humans Magnetic Resonance Imaging Longitudinal Studies Multiple Sclerosis Image Interpretation, Computer-Assisted
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A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.

NeuroImage. Clinical Dec 9, 2019
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of stroke survivors would be a useful aid in patient diagnosis and treatment planning. It would also greatly facilitate the study of brain-behavior relationships by...
Image Interpretation, Computer-Assisted Humans Imaging, Three-Dimensional Magnetic Resonance Imaging Neural Networks, Computer Neuroimaging Stroke Brain
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