Literature DB >> 31278649

Artificial Intelligence in Dermatology-Where We Are and the Way to the Future: A Review.

Daniel T Hogarty1, John C Su2,3, Kevin Phan4, Mohamed Attia5, Mohammed Hossny5, Saeid Nahavandi5, Patricia Lenane6,7, Fergal J Moloney6,7, Anousha Yazdabadi2,8,9,10.   

Abstract

Although artificial intelligence has been available for some time, it has garnered significant interest recently and has been popularized by major companies with its applications in image identification, speech recognition and problem solving. Artificial intelligence is now being increasingly studied for its potential uses in medicine. A sound understanding of the concepts of this emerging field is essential for the dermatologist as dermatology has abundant medical data and images that can be used to train artificial intelligence for patient care. There are already a number of artificial intelligence studies focusing on skin disorders such as skin cancer, psoriasis, atopic dermatitis and onychomycosis. This article aims to present a basic introduction to the concepts of artificial intelligence as well as present an overview of the current research into artificial intelligence in dermatology, examining both its current applications and its future potential.

Entities:  

Year:  2019        PMID: 31278649     DOI: 10.1007/s40257-019-00462-6

Source DB:  PubMed          Journal:  Am J Clin Dermatol        ISSN: 1175-0561            Impact factor:   7.403


  15 in total

1.  A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.

Authors:  Florence Decroos; Sebastian Springenberg; Tobias Lang; Marc Päpper; Antonia Zapf; Dieter Metze; Volker Steinkraus; Almut Böer-Auer
Journal:  Acta Derm Venereol       Date:  2021-08-31       Impact factor: 3.875

Review 2.  Emerging High-Frequency Ultrasound Imaging in Medical Cosmetology.

Authors:  YaPing Tao; Cong Wei; YiMin Su; Bing Hu; Di Sun
Journal:  Front Physiol       Date:  2022-07-04       Impact factor: 4.755

Review 3.  Diagnosing Onychomycosis: What's New?

Authors:  Aditya K Gupta; Deanna C Hall; Elizabeth A Cooper; Mahmoud A Ghannoum
Journal:  J Fungi (Basel)       Date:  2022-04-29

Review 4.  The Importance of Incorporating Human Factors in the Design and Implementation of Artificial Intelligence for Skin Cancer Diagnosis in the Real World.

Authors:  Claire M Felmingham; Nikki R Adler; Zongyuan Ge; Rachael L Morton; Monika Janda; Victoria J Mar
Journal:  Am J Clin Dermatol       Date:  2021-03       Impact factor: 7.403

Review 5.  Review of Machine Learning in Predicting Dermatological Outcomes.

Authors:  Amy X Du; Sepideh Emam; Robert Gniadecki
Journal:  Front Med (Lausanne)       Date:  2020-06-12

6.  Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey.

Authors:  Cherry Sit; Rohit Srinivasan; Ashik Amlani; Keerthini Muthuswamy; Aishah Azam; Leo Monzon; Daniel Stephen Poon
Journal:  Insights Imaging       Date:  2020-02-05

Review 7.  The Application of Artificial Intelligence in the Genetic Study of Alzheimer's Disease.

Authors:  Rohan Mishra; Bin Li
Journal:  Aging Dis       Date:  2020-12-01       Impact factor: 6.745

8.  A Novel Convolutional Neural Network for the Diagnosis and Classification of Rosacea: Usability Study.

Authors:  Zhixiang Zhao; Che-Ming Wu; Chao-Yuan Yeh; Ji Li; Shuping Zhang; Fanping He; Fangfen Liu; Ben Wang; Yingxue Huang; Wei Shi; Dan Jian; Hongfu Xie
Journal:  JMIR Med Inform       Date:  2021-03-15

Review 9.  Dermoscopic features of neoplasms in skin of color: A review.

Authors:  Ekene Ezenwa; Jennifer A Stein; Loren Krueger
Journal:  Int J Womens Dermatol       Date:  2021-01-19

10.  DUNEScan: a web server for uncertainty estimation in skin cancer detection with deep neural networks.

Authors:  Bogdan Mazoure; Alexander Mazoure; Jocelyn Bédard; Vladimir Makarenkov
Journal:  Sci Rep       Date:  2022-01-07       Impact factor: 4.379

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