AIMC Topic:
Image Interpretation, Computer-Assisted

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Utilizing artificial intelligence in endoscopy: a clinician's guide.

Expert review of gastroenterology & hepatology Jun 17, 2020
INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (R &D) is being actively conducted. With the...
Deep Learning Rectal Diseases Endoscopy, Gastrointestinal Helicobacter Infections Humans Stomach Neoplasms Colorectal Neoplasms Image Interpretation, Computer-Assisted Capsule Endoscopy Precancerous Conditions Helicobacter pylori Pharyngeal Neoplasms Gastrointestinal Neoplasms Esophageal Neoplasms Colonic Polyps
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Artificial Intelligence Medical Ultrasound Equipment: Application of Breast Lesions Detection.

Ultrasonic imaging Jun 16, 2020
Breast cancer ranks first among cancers affecting women's health. Our work aims to realize the intelligence of the medical ultrasound equipment with limited computational capability, which is used for the assistant detection of breast lesions. We emb...
Beijing Ultrasonography, Mammary Breast Artificial Intelligence Image Interpretation, Computer-Assisted Humans Databases, Factual Female Breast Neoplasms
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Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading.

Virchows Archiv : an international journal of pathology Jun 15, 2020
The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficu...
Male Prostatic Neoplasms Neoplasm Grading Image Interpretation, Computer-Assisted Observer Variation Humans Artificial Intelligence Databases, Factual
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Automated Lung Ultrasound B-Line Assessment Using a Deep Learning Algorithm.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Jun 15, 2020
Shortness of breath is a major reason that patients present to the emergency department (ED) and point-of-care ultrasound (POCUS) has been shown to aid in diagnosis, particularly through evaluation for artifacts known as B-lines. B-line identificatio...
Image Interpretation, Computer-Assisted Deep Learning Ultrasonography Lung Diseases Video Recording Humans Algorithms Lung
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Electrical Impedance Tomography-Based Abdominal Subcutaneous Fat Estimation Method Using Deep Learning.

Computational and mathematical methods in medicine Jun 11, 2020
This paper proposes a deep learning method based on electrical impedance tomography (EIT) to estimate the thickness of abdominal subcutaneous fat. EIT for evaluating the thickness of abdominal subcutaneous fat is an absolute imaging problem that aims...
Image Interpretation, Computer-Assisted Subcutaneous Fat, Abdominal Humans Computer Simulation Electric Impedance Neural Networks, Computer Tomography, X-Ray Computed Phantoms, Imaging Algorithms Deep Learning Tomography Computational Biology
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Artificial Intelligence in Head and Neck Imaging: A Glimpse into the Future.

Neuroimaging clinics of North America Jun 10, 2020
Artificial intelligence, specifically machine learning and deep learning, is a rapidly developing field in imaging sciences with the potential to improve the efficiency and effectiveness of radiologists. This review covers common technical terms and ...
Humans Artificial Intelligence Tomography, X-Ray Computed Head and Neck Neoplasms Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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Past and present of computer-assisted dermoscopic diagnosis: performance of a conventional image analyser versus a convolutional neural network in a prospective data set of 1,981 skin lesions.

European journal of cancer (Oxford, England : 1990) Jun 10, 2020
BACKGROUND: Convolutional neural networks (CNNs) have shown a dermatologist-level performance in the classification of skin lesions. We aimed to deliver a head-to-head comparison of a conventional image analyser (CIA), which depends on segmentation a...
Predictive Value of Tests Image Interpretation, Computer-Assisted Humans Databases, Factual Prospective Studies Young Adult Adult Cross-Sectional Studies Male Dermoscopy Middle Aged Reproducibility of Results Diagnosis, Computer-Assisted Aged Prognosis Deep Learning Aged, 80 and over Female Adolescent Melanoma Skin Neoplasms
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Artificial intelligence for interpretation of segments of whole body MRI in CNO: pilot study comparing radiologists versus machine learning algorithm.

Pediatric rheumatology online journal Jun 9, 2020
BACKGROUND: To initiate the development of a machine learning algorithm capable of comparing segments of pre and post pamidronate whole body MRI scans to assess treatment response and to compare the results of this algorithm with the analysis of a pa...
Osteitis Pamidronate Tibia Bone Density Conservation Agents Femur Whole Body Imaging Pilot Projects Adolescent Artificial Intelligence Treatment Outcome Machine Learning Support Vector Machine Sensitivity and Specificity Disease Progression Magnetic Resonance Imaging Humans Chronic Disease Radiologists Image Interpretation, Computer-Assisted
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Utilization of a Deep Learning Algorithm for Microscope-Based Fatty Vacuole Quantification in a Fatty Liver Model in Mice.

Toxicologic pathology Jun 8, 2020
Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vessels and bile ducts, is an example where the traditional semiquantitative pathology assessment can be enhanced with artificial intelligence (AI) algorit...
Artificial Intelligence Machine Learning Disease Models, Animal Liver Non-alcoholic Fatty Liver Disease Microscopy Algorithms Animals Deep Learning Mice Image Interpretation, Computer-Assisted Vacuoles
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Applying cascaded convolutional neural network design further enhances automatic scoring of arthritis disease activity on ultrasound images from rheumatoid arthritis patients.

Annals of the rheumatic diseases Jun 5, 2020
OBJECTIVES: We have previously shown that neural network technology can be used for scoring arthritis disease activity in ultrasound images from rheumatoid arthritis (RA) patients, giving scores according to the EULAR-OMERACT grading system. We have ...
Synovitis Middle Aged Severity of Illness Index Female Image Interpretation, Computer-Assisted Humans Ultrasonography Reproducibility of Results Clinical Trials as Topic Neural Networks, Computer Joints Arthritis, Rheumatoid Adult Rheumatology Male
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