Article of the Month – December 2021
December 1, 2021
1941-1950
January 1, 2022Dermatology
AI Smartphone App Could Improve Diagnosis of Psoriasis, Atopic Dermatitis, Eczema
Inflammatory skin diseases have an incidence of around 20% of the population worldwide. They are often diagnosed by “first impression,” leading to significant misdiagnosis, especially psoriasis, eczema, and atopic dermatitis. The artificial intelligence dermatology diagnosis assistant sorts out this problem. Chinese researchers from the Department of Dermatology, Second Xiangya Hospital in Central South University in China, developed a convolutional neural network that analyzed skin images from different patients with healthy skin, psoriasis, eczema, and atopic dermatitis. The model performed a diagnosis for each image among the three categories, and it showed an accuracy of 95.80%. The app is publicly available to doctors in China. The authors noted that the algorithm is already impacting the nation’s health system, with an input of more than 100,000 doctor-taken images. The authors pointed out that the tool will help inexperienced younger doctors and doctors in underdeveloped areas.(1)
Inflammatory skin diseases have an incidence of around 20% of the population worldwide. They are often diagnosed by “first impression,” leading to significant misdiagnosis, especially psoriasis, eczema, and atopic dermatitis. The artificial intelligence dermatology diagnosis assistant sorts out this problem. Chinese researchers from the Department of Dermatology, Second Xiangya Hospital in Central South University in China, developed a convolutional neural network that analyzed skin images from different patients with healthy skin, psoriasis, eczema, and atopic dermatitis.
The model performed a diagnosis for each image among the three categories, and it showed an accuracy of 95.80%. The app is publicly available to doctors in China. The authors noted that the algorithm is already impacting the nation’s health system, with an input of more than 100,000 doctor-taken images. The authors pointed out that the tool will help inexperienced younger doctors and doctors in underdeveloped areas.(1)
New artificial intelligence system can empower medical professionals in diagnosing skin diseases
Deep learning in dermatology is now expanding beyond dermatoscopic recognition of malignancy. Recently, Korean researchers from the Department of Dermatology from the Seoul National University in South Korea trained an AI algorithm to recognize non-neoplastic disorders. This algorithm can precisely categorize cutaneous skin disorders, advise primary treatment options, and serve as a supporting tool to magnify clinicians’ diagnostic accuracy. The researchers gathered 220,000 images of Asian and Caucasian patients with 174 skin diseases and trained neural networks to interpret them. It was discovered that the algorithm could diagnose 134 skin disorders and improve the performance of the medical staff by suggesting primary treatment options and classifying the diseases.(2)
Deep learning in dermatology is now expanding beyond dermatoscopic recognition of malignancy. Recently, Korean researchers from the Department of Dermatology from the Seoul National University in South Korea trained an AI algorithm to recognize non-neoplastic disorders. This algorithm can precisely categorize cutaneous skin disorders, advise primary treatment options, and serve as a supporting tool to magnify clinicians’ diagnostic accuracy.
The researchers gathered 220,000 images of Asian and Caucasian patients with 174 skin diseases and trained neural networks to interpret them. It was discovered that the algorithm could diagnose 134 skin disorders and improve the performance of the medical staff by suggesting primary treatment options and classifying the diseases.(2)
How Robots and A.I. Are About To Change The Industry Forever
TikTok’s nearly 800 million users seek medical advice from random individuals, and Google is also receiving billions of healthcare questions every day. Cara, the new AI-powered tool by the Global Library of Medicine that comprises thousands of dermatology diagnoses, aims to tackle this issue. Cara will be launching at the end of November 2021, marking the first time in our medical history that people can reliably check symptoms online. Another important Autonomous AI platform is 3Derm Triage powered by 3Derm Systems, Inc. systems. The company specializes in providing telemedicine for dermatology by connecting with experts. The company has a second platform for a skin cancer detection tool, 3DermSpot, prepared for FDA clearance. The 3DermSpot was granted an FDA Breakthrough Device designation back in January 2020. (3)
TikTok’s nearly 800 million users seek medical advice from random individuals, and Google is also receiving billions of healthcare questions every day. Cara, the new AI-powered tool by the Global Library of Medicine that comprises thousands of dermatology diagnoses, aims to tackle this issue. Cara will be launching at the end of November 2021, marking the first time in our medical history that people can reliably check symptoms online.
Another important Autonomous AI platform is 3Derm Triage powered by 3Derm Systems, Inc. systems. The company specializes in providing telemedicine for dermatology by connecting with experts. The company has a second platform for a skin cancer detection tool, 3DermSpot, prepared for FDA clearance. The 3DermSpot was granted an FDA Breakthrough Device designation back in January 2020. (3)
AI Breakthrough in Melanoma Detection
Proscia’s DermAI application powered by Proscia software company recently released study results on new technology that uses artificial intelligence to detect melanoma with a high degree of accuracy automictically. These findings may demonstrate the ability of AI to deliver faster diagnoses of any malignant skin pathology, which can improve patient outcomes, physician workload, and lab economics in routine practice. The trial was conducted at Thomas Jefferson University and the University of Florida, where the AI-powered algorithm was used on a set of 1,500 sequential skin biopsies. The technology correctly identified different stages of malignant pathology as invasive melanoma and melanoma in situ with a 93% and 91% sensitivity and specificity, respectively.
DermAI provides an AI-based data set classification for every case, increasing efficiency and quality gains. The application’s performance was tested in different pathology studies, published in a Proscia web, and continues to be validated and deployed as part of the company’s ongoing work in AI.(4)
Proscia’s DermAI application powered by Proscia software company recently released study results on new technology that uses artificial intelligence to detect melanoma with a high degree of accuracy automictically. These findings may demonstrate the ability of AI to deliver faster diagnoses of any malignant skin pathology, which can improve patient outcomes, physician workload, and lab economics in routine practice.
The trial was conducted at Thomas Jefferson University and the University of Florida, where the AI-powered algorithm was used on a set of 1,500 sequential skin biopsies. The technology correctly identified different stages of malignant pathology as invasive melanoma and melanoma in situ with a 93% and 91% sensitivity and specificity, respectively.DermAI provides an AI-based data set classification for every case, increasing efficiency and quality gains. The application’s performance was tested in different pathology studies, published in a Proscia web, and continues to be validated and deployed as part of the company’s ongoing work in AI.(4)
Metabolic Disorders Drugs Market Players Revolutionize Treatment with AI Integration
The majority of companies are focusing on employing AI applications to revolutionize the new treatments of metabolic disorders. This kind of technology radically changes the treatment of cutaneous manifestations of metabolic syndromes: Acne, Dermatitis, Psoriasis, Other Drugs for dermatology diseases. A new way is analyzing large datasets of chemical and biological substances to identify potential drug candidates with higher success rates at a quicker pace when compared to human analysis. 3BIGS (formerly known as 3BIGS CO., LTD.,) a Korean enterprise, is one of the most important companies with biodata analysis studying the relationship between these diseases, targets, and drugs. This AI-based technology helps researchers all around the world to repurpose drugs for different diseases.(5)
The majority of companies are focusing on employing AI applications to revolutionize the new treatments of metabolic disorders. This kind of technology radically changes the treatment of cutaneous manifestations of metabolic syndromes: Acne, Dermatitis, Psoriasis, Other Drugs for dermatology diseases. A new way is analyzing large datasets of chemical and biological substances to identify potential drug candidates with higher success rates at a quicker pace when compared to human analysis.
3BIGS (formerly known as 3BIGS CO., LTD.,) a Korean enterprise, is one of the most important companies with biodata analysis studying the relationship between these diseases, targets, and drugs. This AI-based technology helps researchers all around the world to repurpose drugs for different diseases.(5)
The Rise of Artificial Intelligence in Personalized Skin Care
Although no app can substitute a face-to-face appointment with the dermatologist, AI is the wave of the long run-in skincare. Joshua Zeichner, chief of the division of dermatology at Mount Sinai Healing center in Modern York City, has been working in a couple of dermatologist-approved skincare apps. ModiFace is an expanded reality startup made by dermatologists. It employs AI to perform try-on recreation through photographs or recordings for cosmetics, hair, and skincare. The innovative app can distinguish changes such as dim spots, discoloration, dryness, uneven skin, and rosacea. Moreover, it can visualize the changes recently and after utilizing any product. This feature sheds light on prescribing and eventually offering items personalized to customers’ particular skincare needs.(6)
Although no app can substitute a face-to-face appointment with the dermatologist, AI is the wave of the long run-in skincare. Joshua Zeichner, chief of the division of dermatology at Mount Sinai Healing center in Modern York City, has been working in a couple of dermatologist-approved skincare apps. ModiFace is an expanded reality startup made by dermatologists.
It employs AI to perform try-on recreation through photographs or recordings for cosmetics, hair, and skincare. The innovative app can distinguish changes such as dim spots, discoloration, dryness, uneven skin, and rosacea. Moreover, it can visualize the changes recently and after utilizing any product. This feature sheds light on prescribing and eventually offering items personalized to customers’ particular skincare needs.(6)
Google Unveils Artificial Intelligence Tool for Dermatology
Google (formerly known as Google LLC, Inc.) has been working for three years to design a new tool powered by AI. Recently, they announced the trials to help users understand skin issues, hair, and nails. Once launched, users can use their phone’s camera to take three pictures of their hair, skin, or nail concerns from different positions and angles. The app then asks questions about symptoms to help the tool determine possible causes. The AI algorithm analyzes this information and matches its knowledge of 288 conditions to give users a list of potential explanations. The tool will show dermatologist-reviewed details and answers to commonly asked questions for each possible matching condition. Researchers developed and refined the model with new data encompassing about 65,000 images and case data of diagnosed skin conditions across different demographics.(7)
Google (formerly known as Google LLC, Inc.) has been working for three years to design a new tool powered by AI. Recently, they announced the trials to help users understand skin issues, hair, and nails. Once launched, users can use their phone’s camera to take three pictures of their hair, skin, or nail concerns from different positions and angles. The app then asks questions about symptoms to help the tool determine possible causes.
The AI algorithm analyzes this information and matches its knowledge of 288 conditions to give users a list of potential explanations. The tool will show dermatologist-reviewed details and answers to commonly asked questions for each possible matching condition. Researchers developed and refined the model with new data encompassing about 65,000 images and case data of diagnosed skin conditions across different demographics.(7)
Data used to build algorithms detecting skin disease
Public skin image datasets are increasingly used to develop machine learning algorithms for skin cancer diagnosis and challenging diagnoses. However, these datasets do not include enough information about skin tone; only a minimal number of images are of darker skin. Hence, algorithms built using these datasets might not be as accurate for people who are not white. The study Characteristics of publicly available skin cancer image datasets, a systematic review published in The Lancet Digital Health combined around 100,000 images, but only 2,236 had information about different skin colors. Creators of public datasets mentioned that new images can always be added, and researchers want to see more examples of conditions on darker skin. Similarly, improving the transparency and clarity of all datasets will help researchers track progress toward more diverse sets that could lead to more equitable AI tools.(8)
Public skin image datasets are increasingly used to develop machine learning algorithms for skin cancer diagnosis and challenging diagnoses. However, these datasets do not include enough information about skin tone; only a minimal number of images are of darker skin. Hence, algorithms built using these datasets might not be as accurate for people who are not white.
The study Characteristics of publicly available skin cancer image datasets, a systematic review published in The Lancet Digital Health combined around 100,000 images, but only 2,236 had information about different skin colors. Creators of public datasets mentioned that new images can always be added, and researchers want to see more examples of conditions on darker skin. Similarly, improving the transparency and clarity of all datasets will help researchers track progress toward more diverse sets that could lead to more equitable AI tools.(8)
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