Artificial Intelligence (AI) In Dermatology Diagnosis Market Size, Share, Opportunities, And Trends By Type (Standalone AI systems, AI-powered mobile Apps), By Technology (Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), Others), By Application (Skin Cancer Diagnosis, Acne And Rosacea Diagnosis, Psoriasis Diagnosis, Eczema Diagnosis, Hair And Nail Disorders Diagnosis, Others), By End-User (Hospitals And Clinics, Dermatology Clinics And Centers, Research Institutes And Academic Centers, Others), And By Geography - Forecasts From 2024 To 2029

The Artificial Intelligence (AI) in the dermatology diagnosis market is expected to grow at a CAGR of 25.43%, reaching a market size of US$630.883 million in 2029 from US$203.208 million in 2024.

The demand for AI-based dermatology diagnosis services is expected to grow steadily. AI in dermatology diagnosis is set to transform dermatological services, i.e., AI will be applied to diagnose and treat dermatological conditions. The situation becomes worse as skin diseases are rising worldwide, thus increasing the demand for quick and precise diagnosis. Dermatological systems that use AI technology explore vast repositories of medical images through sophisticated algorithms for faster and more effective diagnosis and classification of skin issues. These technologies enable dermatologists to provide more accurate diagnoses, enhancing treatment methods and successful healthcare results tailored to individual patients. As technological developments escalate, the demand for AI in dermatology diagnosis is expected to grow tremendously, offering a better treatment option for dermatological services and increasing the management scope of skin diseases.

Artificial Intelligence (AI) in Dermatology Diagnosis Market Drivers:

• Increasing prevalence of skin disorders enhances the AI in dermatology diagnosis market growth

The market for AI in dermatology diagnosis is growing significantly due to the increased prevalence of skin-related issues globally. Skin disorders, as the World Health Organisation (WHO) points out, affect the lives of most people, and an estimated 900 million people have skin diseases at any time. Health conditions like acne, psoriasis, and malignant skin tumors are serious public health issues and require an accurate and timely diagnosis. Using AI in dermatology to analyze large amounts of clinical photographs, such advanced dermatological solutions assist healthcare experts in formulating a more accurate diagnosis. With the rising occurrence of skin disorders, the emphasis on AI-based dermatology therapeutics will continue to grow significantly, boosting the AI in dermatology diagnosis market growth.

• Rising demand for efficient and accurate diagnoses pushes AI in the dermatology diagnosis market growth.

The utilization of AI in dermatology diagnostic purposes is rising due to the strong need for precise and timely diagnosis. AI and dermatology are part of the basic healthcare services research needs due to the desire to improve diagnosis quickly and more effectively. These systems can process and analyze millions of medical images in a very short time, enabling the diagnosis of many types of skin lesions. Consequently, with the demand for accurate and fast diagnoses from healthcare givers and patients, there will be an increase in the application of AI in the dermatology diagnosis market.

• Growing adoption of telemedicine and remote dermatology services boosts the AI in dermatology diagnosis market size.

The AI in the dermatology diagnosis market is seeing rapid expansion because of the increased usage of telemedicine and remote dermatological services. The introduction of telemedicine components with AI-oriented dermatology solutions has made it possible for dermatologists to evaluate skin conditions, provide consultations, and even make diagnoses to patients across a wide geographical spectrum. Owing to the easy and affordable nature of remote dermatology services and the wisdom of AI in aiding accurate diagnosis, the adoption of AI in dermatology diagnosis has been accelerated. This has made restrictive dermatological services available to patients worldwide.

• AI's potential in expanding access to dermatological care propels AI in the dermatology diagnosis market.

AI in the dermatology diagnosis market is rapidly garnering momentum because dermatological treatments can now be easily accessible to many people. A study published in the Journal of Investigative Dermatology reported an accuracy of 95% in skin cancer recognition by AI algorithms, which is the same as the reported accuracy for dermatologists. AI-powered dermatology solutions can lessen the gap between dermatological practitioners and marginalized regions, thus improving the quality of care.

According to the World Health Organisation, over 30% of skin problems in low-income nations are misdiagnosed or untreated. AI's ability to give efficient and accurate diagnostics remotely makes it vital for democratizing dermatological care and ensuring patients in rural or underserved locations receive prompt and accurate assessments.

Artificial Intelligence (AI) in Dermatology Diagnosis Market Restraints:

• High costs and human resistance are anticipated to impede market growth

Undergoing aesthetic procedures, patients face a certain number of risks, including the risk of infection, an allergic reaction on the skin, changes in pigmentation, injuring internal organs, and risks associated with anesthesia. Some studies have reported that red light therapy devices may be linked to blistering and burning injuries. While some have claimed to have been burned by corroded equipment or faulty wiring, very few have reported getting burned after sleeping with the unit on. These problems are expected to impede the application of dermatological treatments.

Artificial Intelligence (AI) in Dermatology Diagnosis Market Geographical Outlook

• North America is witnessing exponential growth during the forecast period

This region is the global leader for several reasons, such as well-developed healthcare systems, highly mobile technology, and high investments in AI. North America has remained home to many established players and new entrants who develop AI-based dermatological solutions that promote innovation and increase the market size. In addition, the rising prevalence of skin diseases in the region and the growing demand for quick and accurate dermatological diagnosis have contributed to the increasing adoption of AI solutions in dermatology. North America’s focus on technological advancements and commitment to the enhancement of dermatological care has subjugated the region in the AI in dermatology diagnosis market.

Artificial Intelligence (AI) in Dermatology Diagnosis Market Key Launches

• In April 2024, researchers at the Stanford Center for Digital Health found that using deep learning-powered AI algorithms increases the accuracy of skin cancer diagnostics for physicians, nurse practitioners, and medical students.
• In April 2022, a global medical AI company, VUNO, partnered with the Mayo Clinic. This research collaboration encouraged both organizations to improve precision oncology technologies that are driven by AI treatment, which was signed by VUNO chief executive officer Lee Yeha. Under this research partnership, Mayo Clinic worked with VUNO on novel applications of AI and machine learning techniques in cancer diagnosis, prognosis, and therapy stratification. This partnership enhanced VUNO's AI R&D capabilities by providing access to the Mayo Clinic's AI research, clinical expertise, and infrastructure. This enabled the development of numerous predictive and prognostic biomarkers for better treatment outcomes in cancer patients.

The Artificial Intelligence (AI) In dermatology diagnosis market is segmented and analyzed as follows:

• By Type
  • Standalone AI Systems
  • AI-Powered Mobile Apps                          
• By Technology
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Natural Language Processing (NLP)
  • Others             
• By Application
  • Skin Cancer Diagnosis
  • Acne And Rosacea Diagnosis
  • Psoriasis Diagnosis
  • Eczema Diagnosis
  • Hair And Nail Disorders Diagnosis
  • Others                       
• By End-User
  • Hospitals And Clinics
  • Dermatology Clinics And Centers
  • Research Institutes And Academic Centers
  • Others          
•  By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain    
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Others
  • Asia Pacific
    • Japan
    • China
    • India
    • South Korea
    • Indonesia
    • Taiwan
    • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. CXO Perspective

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. ARTIFICIAL INTELLIGENCE (AI) IN DERMATOLOGY DIAGNOSIS MARKET BY TYPE

5.1. Introduction

5.2. Standalone AI Systems

5.3. AI-Powered Mobile Apps 

6. ARTIFICIAL INTELLIGENCE (AI) IN DERMATOLOGY DIAGNOSIS MARKET BY TECHNOLOGY 

6.1. Introduction

6.2. Machine Learning

6.3. Deep Learning

6.4. Computer Vision

6.5. Natural Language Processing (NLP)

6.6. Others

7. ARTIFICIAL INTELLIGENCE (AI) IN DERMATOLOGY DIAGNOSIS MARKET BY APPLICATION

7.1. Introduction

7.2. Skin Cancer Diagnosis

7.3. Acne And Rosacea Diagnosis

7.4. Psoriasis Diagnosis

7.5. Eczema Diagnosis

7.6. Hair And Nail Disorders Diagnosis

7.7. Others

8. ARTIFICIAL INTELLIGENCE (AI) IN DERMATOLOGY DIAGNOSIS MARKET BY END-USER

8.1. Introduction

8.2. Hospitals And Clinics

8.3. Dermatology Clinics and Centers

8.4. Research Institutes and Academic Centers

8.5. Others

9. ARTIFICIAL INTELLIGENCE (AI) IN DERMATOLOGY DIAGNOSIS MARKET BY GEOGRAPHY

9.1. Introduction

9.2. North America

9.2.1. By Type

9.2.2. By Technology

9.2.3. By Application

9.2.4. BY End-User 

9.2.5. By Country

9.2.5.1. United States

9.2.5.2. Canada

9.2.5.3. Mexico

9.3. South America

9.3.1. By Type

9.3.2. By Technology

9.3.3. By Application

9.3.4. BY End-User 

9.3.5. By Country

9.3.5.1. Brazil

9.3.5.2. Argentina

9.3.5.3. Others

9.4. Europe

9.4.1. By Type

9.4.2. By Technology

9.4.3. By Application

9.4.4. BY End-User 

9.4.5. By Country

9.4.5.1. United Kingdom

9.4.5.2. Germany

9.4.5.3. France

9.4.5.4. Italy

9.4.5.5. Spain    

9.4.5.6. Others

9.5. Middle East and Africa

9.5.1. By Type

9.5.2. By Technology

9.5.3. By Application

9.5.4. BY End-User 

9.5.5. By Country

9.5.5.1. Saudi Arabia

9.5.5.2. UAE

9.5.5.3. Others

9.6. Asia Pacific

9.6.1. By Type

9.6.2. By Technology

9.6.3. By Application

9.6.4. BY End-User 

9.6.5. By Country

9.6.5.1. Japan

9.6.5.2. China

9.6.5.3. India

9.6.5.4. South Korea

9.6.5.5. Indonesia

9.6.5.6. Taiwan

9.6.5.7. Others

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

10.1. Major Players and Strategy Analysis

10.2. Market Share Analysis

10.3. Mergers, Acquisitions, Agreements, and Collaborations

10.4. Competitive Dashboard

11. COMPANY PROFILES

11.1. 3derm Systems, Inc.

11.2. Aidoc Medical Ltd.

11.3. Aidoc

11.4. Arterys Inc.

11.5. Beijing Infervision Technology Co., Ltd.

11.6. Butterfly Network, Inc.

11.7. Enlitic, Inc.

11.8. Fdna Inc.

11.9. Ibm Corporation

11.10. Mirada Medical Limited

3derm Systems, Inc.

Aidoc Medical Ltd.

Aidoc

Arterys Inc.

Beijing Infervision Technology Co., Ltd.

Butterfly Network, Inc.

Enlitic, Inc.

Fdna Inc.

Ibm Corporation

Mirada Medical Limited