Ofir Selinger | 11/01/2023
Challenge Name
Dermatology Track
Research Inquiries
Existing applications on the market (worldwide).
Findings
Current technologies and solutions:
AI driven technology utilizing big data and deep learning to create automated decision support in diagnostics and therapeutics of dermatology. DermaDetect is a developer of algorithm-based digital image analyzing solutions for the diagnosis of skin disorders. The company is developing a non-intrusive detecting and monitoring solution for medical and healthcare applications for the detection of skin disorders. It is also developing a solution for consumer and non-medical professionals to self-detect and track skin disorders.
AI Dermatologist uses a deep machine learning algorithm (AI-algorithm) which was trained by confirmed diagnosed (by dermatologists) dermoscopic imaging database. The AI is able to distinguish between benign and malignant tumors, find risks of human papillomavirus, and classify different types of acne.
This mobile app gives a diagnosis solely on moles using a trained AI algorithm but combines it with a dermatologist second opinion.
Additional Information:
Non-diagnostic apps using AI on skin photos, giving a quick analysis:
DermAssist (by Google Health)
Aysa – helps in “correction before sending to doctors”
MIISKIN – has an automatic skin imaging and image modifications.
Data collector for Teledermatology (Telehealth in dermatology):
Mobile App and clinician dashboard for conducting remote physical exams, reviewing exam data, and communicating with patients. AI-powered guidance technology ensures anyone can capture exam data safely and accurately. It also takes skin pictures for later adivasatory meeting with your dermatologist.
Collect picturs to dermatologists, like tyto but focused on skin and have a Mole spector AddOn device.
Database of pictures after guiding questions:
Dermatology Database, The Cunliffe (TP) General Dermatology Diagnostic Tool, DermaDiag by Dermnet.
Literature review of technologies, approaches and solutions:
A medical comprehensive Review (November 2022) of AI trends in Dermatology Image Analysis show, among an abundance of information, on market aid-dermatology AI system and apps:
Table 5.
Name | Manufacturer | Country | On Market Year | Platform | Application | Reference |
Moleanalyzer pro | Fotofinder | Germany | 2018 | Windows | Analyzes melanocytic as well as non-melanocytic skin lesions and calculates an AI score for mole risk assessment | |
Vectra WBS 360 | Canfiield | USA | 2017 | Windows | Capturing the entire skin surface in macro quality resolution with a single capture, to identify and monitors pigment lesions automatically or mannually | |
Visia skin | Canfiield | USA | 2007 | Windows | Capturing key visual information for eight areas affecting complexion health and appearance and to provide an informative comparison of patient’s complexion’s characteristics to others of same age and skin type | |
Antera 3D | Miravex | Ireland | 2011 | Windows | Analysis and measurement of wrinkles, texture, pigmentation, redness and other lesions | [176] |
Dermoscan X2 | Dermoscan | Germany | 2017 | Windows | Identification of the new or modified lesions with digital photo documentations and makes automatic comparison of pigmentation marks | [177] |
AIDERMA | Dingxiangyuan | China | 2018 | Online | Automatic identification of skin disorders and stores patient’s medical record in the cloud safely | |
DermEngine | MetaOptima Technology Inc. | Canada | 2015 | Android and iOS | Imaging, documentation and analysis of skin conditions including skin cancer; offers business intelligence features designed for practice management | [71] |
Skin-App | Swiss4ward | Switzerland | 2017 | Android and iOS | Detection of hand eczema automatically | [71] |
Neurodermitis Helferin|Nia | Nia Health | Germany | 2019 | Android and iOS | Marks affected areas on the clear body diagram, takes photos and documents of the current severity of the neurodermatitis and gives personalized suggestions after further analysis | [157] |
DermoScanner | Neat Technology lnc. | N/A | 2019 | Android | Analysis of skin moles and detects skin cancers at an early stage when it is most treatable. | [159] |
Dermacompass | Swiss4ward | Switzerland | 2017 | Android and iOS | It contains skin diseases, pictures and algorithms for treatment and provides individual case diagnosis and image comparison for dermatologists | [180] |
Moreover in the same article you’ll find the “behind the scenes” of the AI dermatology field including: The algorithm model (key technologies like GAN, CNN, DNN and ANN), its purpose, the dataset used and its sensitivity and specificity,
Latest Review (December 2022) of Dermatology AI, discusses the gap between breakthroughs in vision AI and the applicability of it in everyday clinical practice. It covers regulation, challenges, and possible solutions for overcoming limitations in future studies.
A Recent scientific Review (2020) of “Use of Artificial Intelligence in Dermatology” introduces us new developments of AI relevant to dermatology, and exams its current and future implementation.
References:
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7640800/
- https://www.dermadetect.com/about.aspx
- https://ai-derm.com/
- https://apps.apple.com/us/app/scanoma-mole-check/id1478978663
- https://www.mdpi.com/2077-0383/11/22/6826
- https://pubmed.ncbi.nlm.nih.gov/36306100/
- https://health.google/consumers/dermassist/
- https://askaysa.com/
- https://apps.apple.com/us/app/miiskin-skin-dermatology/id1214795331
- https://apps.apple.com/us/app/rash-id-rash-identifier/id1488063716
- https://www.tytocare.com/products/tytohome/
- https://www.dermengine.com/molescope?__hstc=62383603.c49150c53ca211aa6cd2423b6bf7e5f4.1673435031235.1673435031235.1673435031235.1&__hssc=62383603.2.1673435031235&__hsfp=1576218530
- https://apps.apple.com/us/app/dermatology-database/id1464798679
- https://www.pcds.org.uk/general-dermatology-table
- https://dermnetnz.org/dermdiag#:~:text=The%20DermDiag%20Tool%20is%20designed,unfamiliar%20with%20any%20dermatological%20terms.