AIMC Topic: Dermatology

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Artificial Intelligence in Medicine: Where Are We Now?

Academic radiology Oct 19, 2019
Artificial intelligence in medicine has made dramatic progress in recent years. However, much of this progress is seemingly scattered, lacking a cohesive structure for the discerning observer. In this article, we will provide an up-to-date review of ...
Artificial Intelligence Forecasting Radiography Ophthalmology Radiology Dermatology Pathology
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A superpixel-driven deep learning approach for the analysis of dermatological wounds.

Computer methods and programs in biomedicine Sep 13, 2019
BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi...
Humans Machine Learning Image Processing, Computer-Assisted Skin Ulcer Support Vector Machine Dermatology Area Under Curve Pattern Recognition, Automated Bayes Theorem Principal Component Analysis Algorithms Diagnosis, Computer-Assisted Reproducibility of Results Deep Learning Sensitivity and Specificity
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Natural language processing of Reddit data to evaluate dermatology patient experiences and therapeutics.

Journal of the American Academy of Dermatology Jul 12, 2019
BACKGROUND: There is a lack of research studying patient-generated data on Reddit, one of the world's most popular forums with active users interested in dermatology. Techniques within natural language processing, a field of artificial intelligence, ...
Natural Language Processing Feasibility Studies Dermatology Psoriasis Social Media Sunbathing Patient Outcome Assessment Acne Vulgaris Humans Reproducibility of Results Cluster Analysis Software
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Commentary: Position statement on augmented intelligence (AuI).

Journal of the American Academy of Dermatology Jun 25, 2019
Practice Guidelines as Topic Humans Algorithms Dermatology Artificial Intelligence
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Artificial intelligence, machine learning and deep learning: definitions and differences.

Clinical and experimental dermatology Jun 24, 2019
Terminology as Topic Machine Learning Deep Learning Dermatology Artificial Intelligence
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Artificial intelligence in dermato-oncology: a joint clinical and data science perspective.

International journal of dermatology May 31, 2019
Humans Skin Neoplasms Deep Learning Melanoma Datasets as Topic Dermatology Image Interpretation, Computer-Assisted Data Science Medical Oncology Early Detection of Cancer
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Augmented Intelligence in Dermatology: Fantasy or Future?

Dermatology (Basel, Switzerland) Mar 19, 2019
Dermatology Algorithms Skin Diseases Humans Artificial Intelligence
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A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.

European journal of cancer (Oxford, England : 1990) Mar 8, 2019
BACKGROUND: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively ...
Image Interpretation, Computer-Assisted Sensitivity and Specificity Dermatologists Dermatology Skin Neoplasms Humans Dermoscopy Neural Networks, Computer Melanoma
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The role of public challenges and data sets towards algorithm development, trust, and use in clinical practice.

Seminars in cutaneous medicine and surgery Mar 1, 2019
In the past decade, machine learning and artificial intelligence have made significant advancements in pattern analysis, including speech and natural language processing, image recognition, object detection, facial recognition, and action categorizat...
Benchmarking Dermatology Humans Machine Learning Algorithms Artificial Intelligence
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Artificial intelligence and dermatology: opportunities, challenges, and future directions.

Seminars in cutaneous medicine and surgery Mar 1, 2019
The application of artificial intelligence (AI) to medicine has considerable potential within dermatology, where the majority of diagnoses are based on visual pattern recognition. Opportunities for AI in dermatology include the potential to automate ...
Humans Artificial Intelligence Forecasting Reproducibility of Results Dermatology
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