AIMC Topic: Dermatologists

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Performance of a deep learning-based application for the diagnosis of basal cell carcinoma in Indian patients as compared to dermatologists and nondermatologists.

International journal of dermatology Oct 11, 2020
Skin Neoplasms Carcinoma, Basal Cell Deep Learning Dermatologists Dermatology Humans
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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...
Artificial Intelligence Melanoma Skin Neoplasms Dermoscopy Surveys and Questionnaires Humans Diagnostic Imaging Internet Dermatologists
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Prospective, comparative evaluation of a deep neural network and dermoscopy in the diagnosis of onychomycosis.

PloS one Jun 11, 2020
BACKGROUND: Onychomycosis is the most common nail disorder and is associated with diagnostic challenges. Emerging non-invasive, real-time techniques such as dermoscopy and deep convolutional neural networks have been proposed for the diagnosis of thi...
Diagnosis, Computer-Assisted Deep Learning Humans Computer Systems Adult Hydroxides Predictive Value of Tests Foot Dermatoses Neural Networks, Computer Potassium Compounds Dermatologists Algorithms Onychomycosis Mycological Typing Techniques Diagnostic Errors Prospective Studies Male Photography Female Middle Aged Dermoscopy Young Adult
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A deep learning system for differential diagnosis of skin diseases.

Nature medicine May 18, 2020
Skin conditions affect 1.9 billion people. Because of a shortage of dermatologists, most cases are seen instead by general practitioners with lower diagnostic accuracy. We present a deep learning system (DLS) to provide a differential diagnosis of sk...
Humans Female Adult Male Middle Aged Deep Learning Indians, North American Melanoma Skin Neoplasms Carcinoma, Basal Cell Carcinoma, Squamous Cell Warts Dermatitis, Seborrheic Folliculitis Alaska Natives Native Hawaiian or Pacific Islander Black or African American Eczema Hispanic or Latino Acne Vulgaris Telemedicine Asian Psoriasis White People Photography Diagnosis, Differential Physicians, Primary Care Nurse Practitioners Dermatologists Keratosis, Seborrheic Skin Diseases
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Deep learning for dermatologists: Part I. Fundamental concepts.

Journal of the American Academy of Dermatology May 17, 2020
Artificial intelligence is generating substantial interest in the field of medicine. One form of artificial intelligence, deep learning, has led to rapid advances in automated image analysis. In 2017, an algorithm demonstrated the ability to diagnose...
Dermatologists Humans Artificial Intelligence Algorithms Skin Neoplasms Deep Learning
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Deep learning for dermatologists: Part II. Current applications.

Journal of the American Academy of Dermatology May 16, 2020
Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial in...
Radiography Radiology Dermatologists Humans Artificial Intelligence Deep Learning
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Augmented Intelligence Dermatology: Deep Neural Networks Empower Medical Professionals in Diagnosing Skin Cancer and Predicting Treatment Options for 134 Skin Disorders.

The Journal of investigative dermatology Mar 31, 2020
Although deep learning algorithms have demonstrated expert-level performance, previous efforts were mostly binary classifications of limited disorders. We trained an algorithm with 220,680 images of 174 disorders and validated it using Edinburgh (1,3...
Datasets as Topic Photography Internship and Residency Drug Therapy, Computer-Assisted Dermatologists Skin Diseases Dermatology Image Interpretation, Computer-Assisted Antiviral Agents Antifungal Agents Skin Feasibility Studies Young Adult Anti-Bacterial Agents Adult Female Male Skin Neoplasms Middle Aged Humans Dermoscopy Aged Glucocorticoids Deep Learning Clinical Competence Adolescent ROC Curve
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Artificial intelligence and melanoma detection: friend or foe of dermatologists?

British journal of hospital medicine (London, England : 2005) Jan 28, 2020
The significance of early diagnosis for melanoma prognosis and survival cannot be understated. The public health benefits of melanoma prevention and detection have driven advances in diagnostics for skin cancer, particularly in the field of artificia...
Early Detection of Cancer Dermatologists Diffusion of Innovation Humans Artificial Intelligence Melanoma
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Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 21, 2020
BACKGROUND: Deep learning convolutional neural networks (CNN) may assist physicians in the diagnosis of melanoma. The capacity of a CNN to differentiate melanomas from combined naevi, the latter representing well-known melanoma simulators, has not be...
Aged Young Adult Adult Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Clinical Competence Female Melanoma Skin Neoplasms Dermoscopy Dermatologists Humans Melanocytes Nevus, Pigmented
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Superior skin cancer classification by the combination of human and artificial intelligence.

European journal of cancer (Oxford, England : 1990) Sep 10, 2019
BACKGROUND: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. Howe...
Skin Neoplasms Humans Image Interpretation, Computer-Assisted Dermoscopy Neural Networks, Computer Deep Learning Observer Variation Algorithms Dermatologists Prognosis
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