AIMC Topic: Diagnostic Imaging

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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.

Neuroimaging clinics of North America Sep 17, 2020
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolut...
Artificial Intelligence Machine Learning Brain Humans Hemorrhagic Stroke Diagnostic Imaging Image Interpretation, Computer-Assisted Neuroimaging United States Triage
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[Artificial intelligence for eye care].

Nederlands tijdschrift voor geneeskunde Sep 17, 2020
Technological developments in ophthalmic imaging and artificial intelligence (AI) create new possibilities for diagnostics in eye care. AI has already been applied in ophthalmic diabetes care. AI-systems currently detect diabetic retinopathy in gener...
Mass Screening Diagnostic Imaging Sensitivity and Specificity General Practice Macular Degeneration Glaucoma Artificial Intelligence Algorithms Humans Diabetic Retinopathy
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Developing an AI project.

Journal of medical imaging and radiation sciences Sep 15, 2020
Artificial intelligence applications can very powerful in areas of speech recognition, image processing and identification, medical diagnosis and clustering to name a few. There is a perception that developing your own artificial intelligence (AI) ap...
Humans Artificial Intelligence Image Processing, Computer-Assisted Diagnostic Imaging
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Thyroid Incidentalomas: Practice Considerations for Radiologists in the Age of Incidental Findings.

Radiologic clinics of North America Sep 14, 2020
Radiologists very frequently encounter incidental findings related to the thyroid gland. Given increases in imaging use over the past several decades, thyroid incidentalomas are increasingly encountered in clinical practice, and it is important for r...
Practice Guidelines as Topic Immunohistochemistry Ultrasonography, Doppler Positron Emission Tomography Computed Tomography Radiologists Incidental Findings Biopsy, Needle Thyroid Neoplasms Thyroid Nodule Magnetic Resonance Imaging Diagnostic Imaging Female United States Humans Male Artificial Intelligence Incidence Clinical Decision-Making
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Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.

Journal of medical Internet research Sep 11, 2020
BACKGROUND: Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagnostic studies have revealed the superiority of artificial intelligence (AI) in classifying dermoscopic images of melanoma and nevi, concluding that th...
Melanoma Skin Neoplasms Dermoscopy Humans Artificial Intelligence Dermatologists Diagnostic Imaging Internet Surveys and Questionnaires
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Inconsistency in the use of the term "validation" in studies reporting the performance of deep learning algorithms in providing diagnosis from medical imaging.

PloS one Sep 11, 2020
BACKGROUND: The development of deep learning (DL) algorithms is a three-step process-training, tuning, and testing. Studies are inconsistent in the use of the term "validation", with some using it to refer to tuning and others testing, which hinders ...
Validation Studies as Topic Journal Impact Factor Algorithms Diagnostic Imaging Periodicals as Topic Humans Machine Learning
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Medical Imaging of Microrobots: Toward Applications.

ACS nano Sep 10, 2020
Medical microrobots (MRs) have been demonstrated for a variety of non-invasive biomedical applications, such as tissue engineering, drug delivery, and assisted fertilization, among others. However, most of these demonstrations have been carried out i...
Robotics Diagnostic Imaging
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Advancing Medical Imaging Informatics by Deep Learning-Based Domain Adaptation.

Yearbook of medical informatics Aug 21, 2020
INTRODUCTION: There has been a rapid development of deep learning (DL) models for medical imaging. However, DL requires a large labeled dataset for training the models. Getting large-scale labeled data remains a challenge, and multi-center datasets s...
Diagnostic Imaging Medical Informatics Humans Machine Learning Deep Learning
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Using autoencoders as a weight initialization method on deep neural networks for disease detection.

BMC medical informatics and decision making Aug 20, 2020
BACKGROUND: As of today, cancer is still one of the most prevalent and high-mortality diseases, summing more than 9 million deaths in 2018. This has motivated researchers to study the application of machine learning-based solutions for cancer detecti...
Neoplasms Deep Learning Diagnostic Imaging Gene Expression Early Detection of Cancer Humans Neural Networks, Computer Machine Learning
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Position paper on COVID-19 imaging and AI: From the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare.

Medical image analysis Aug 19, 2020
In this position paper, we provide a collection of views on the role of AI in the COVID-19 pandemic, from clinical requirements to the design of AI-based systems, to the translation of the developed tools to the clinic. We highlight key factors in de...
SARS-CoV-2 Diagnostic Imaging Artificial Intelligence Coronavirus Infections COVID-19 Betacoronavirus Humans Pandemics Algorithms Pneumonia, Viral
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