Will Artificial Intelligence be a Transformative Solution for Dermatological Care in Resource-Limited Settings?

Will Artificial Intelligence be a Transformative Solution for Dermatological Care in Resource-Limited Settings? | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 18 April 2025 V1 Latest version Share on Will Artificial Intelligence be a Transformative Solution for Dermatological Care in Resource-Limited Settings? Authors : Najia Sadiq1 0009-0001-7796-3580 [email protected] , Osaid Ahmed1 , Tooba Ali 0000-0003-1867-943X , and Zainab Muhammad Hanif3 Authors Info & Affiliations https://doi.org/10.22541/au.174500834.40311564/v1 192 views 113 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Quality healthcare is a major challenge around the world, particularly in developing countries, and this concern applies to dermatology as well. Many communities in such environments lack adequate medical infrastructure leaving behind patients in dire need to get treatments. Many people with skin conditions either do not receive treatment or wait so long that their symptoms worsen, which drastically reduces their quality of life. Artificial intelligence (AI) could be a viable solution for this concern.AI-based tools, particularly picture recognition algorithms, can detect common dermatological illnesses. AI-powered smartphone apps can also allow patients to upload photos of their skin problems and receive treatments. Moreover, AI-powered telemedicine solutions can eliminate the need for city-based specialists by enabling general practitioners in remote areas to get prompt support. This model has the potential to be scaled and replicated in resource-limited areas, effectively addressing the dermatological care gap through digital health technologies. The focus should be placed on the cost and accessibility of these technologies to bridge the gap between underserved populations and their necessary treatments. Article type: Letter to the Editor Title: Will Artificial Intelligence be a Transformative Solution for Dermatological Care in Resource-Limited Settings? Running title: AI in dermatopathology AUTHORS: Najia Sadiq 1 , Osaid Ahmed 1 , Tooba Ali 2 , Zainab Muhammad Hanif 3 1 Jinnah Sindh Medical University 2 Dow University of Health Sciences 3 Shaheed Mohtarma Benazir Bhutto Medical College Corresponding author and Co-author-1: Najia Sadiq Affiliation: Jinnah Sindh Medical University Address: V22W+F2H، Rafiqui H.J, Iqbal Shaheed Rd, Karachi Cantonment Karachi, Karachi City, Sindh 75510 Telephone number: 03378012987 Email address: [email protected] ORCID: 0009-0001-7796-3580 Co-author-2: Osaid Ahmed: Affiliation: Jinnah Sindh Medical University Address: V22W+F2H، Rafiqui H.J, Iqbal Shaheed Rd, Karachi Cantonment Karachi, Karachi City, Sindh 75510 Email address: [email protected] Co-author-3: Tooba Ali: Affiliation: Dow University of Health Sciences Address: Mission Road, Karachi, Pakistan Email address: [email protected] ORCID: 0000-0003-1867-943X Co-author-4: Zainab Muhammad Hanif: Affiliation: Shaheed Mohtarma Benazir Bhutto Medical College Address: VXFW+42F, Lyari Hospital Rd, Rangiwara Lyari, Karachi, 75660 Email address: [email protected] Funding information : None Conflicts of Interest : None declared. Ethical Approval: none required Ethics statement: Not applicable Data availability statement : Not applicable Manuscript word count : 599 words [excluding references] References : 6 Figures: 0 Tables: 0 Keywords: dermatology; artificial intelligence; Quality Healthcare; Resource-Limited Settings Main text Dear Editor, Quality healthcare is a major challenge around the world, particularly in developing countries, and this concern applies to dermatology as much as it does to any specialty. Many communities in such environments lack adequate medical infrastructure. It is challenging for people to get the treatment they need in many of these places since there are insufficient facilities and qualified personnel. Many people with skin conditions either do not receive treatment or wait so long that their symptoms worsen, which drastically reduces their quality of life. In dermatology, epidemic illnesses are becoming more significant. These range from serious issues like malignancies to everyday concerns like eczema and acne. Furthermore, the cosmetics industry’s explosive growth is putting an increasing strain on medical professionals. [1] Unfortunately, many people are forced to travel for specialized care due to limited access and waiting in crowded hospitals. Addressing these evolving public health issues is a major concern.Artificial intelligence (AI) could be a viable answer to this dilemma. AI-based diagnosis tools, particularly picture recognition algorithms, can detect common dermatological illnesses with high accuracy. AI-powered smartphone apps can also allow patients to upload photos of their skin problems and receive preliminary diagnoses and therapy recommendations. Moreover, AI-powered telemedicine solutions can eliminate the need for city-based specialists by enabling general practitioners in remote areas to get prompt support from AI algorithms. The impact of AI on medical imaging is already changing the way diagnoses are made. For example, using primary tumour slides of cutaneous squamous cell carcinoma, Knuutila et al. developed a supervised ResNet architecture to predict the risk of metastasis. [2] Deep learning algorithms, a type of AI, are aiding in accurately diagnosing the skin diseases using photographs of rashes, lesions, and other dermatological conditions. [3]According to X Du Harpur’s research, machine learning automated processes by using algorithms to identify patterns and learn from data. [4]. Key methods include deep learning, neural networks, supervised learning, and convolutional neural networks. [4]. Implementing a digital laboratory workflow, artificial intelligence (AI)-based assistance tools, and whole slide images (WSI)-based training programs will aid in patients’ diagnosis and treatment. Digitalization in dermatopathology revolutionizes operations but also poses challenges that need addressing. [5] A study conducted by Peracca SB et al. [6] demonstrated the efficacy of tele dermatology hubs in expanding access to dermatological care in developing countries and regions where such care is limited. Establishing tele dermatology centres in strategic locations, along with mobile screening units and collaborations, can significantly improve the delivery of dermatological services in underserved communities. These hubs can serve as focal points for AI-powered diagnostic tools, high-speed internet access, and healthcare professionals.AI-assisted skin checks could be provided to patients in rural areas, enabling them to access specialists for accurate diagnoses, personalized treatment plans, and aftercare via telemedicine. This model has the potential to be scaled and replicated in other resource-limited areas, effectively addressing the dermatological care gap through digital health technologies.Collaboration between policymakers, medical organizations, and technology entrepreneurs is needed to realize this vision and reach our goal. The government needs to make regulations on how to introduce AI into the healthcare ecosystem focusing on eliminating such barriers in terms of funding, infrastructure, ordinances, and such. The future growth of these technologies will depend on partnerships between public and private entities as well as government initiatives for the betterment of people in underserved areas. The focus should be placed on the cost and accessibility of these technologies to bridge the gap between underserved populations and necessary treatments, as many individuals in these areas are unable to receive care due to inadequate policies and resources. STATEMENTS AND DECLARATIONS : Ethical Approval: Not applicable Competing Interests: None Funding: None Availability of data and materials: No datasets were generated or analysed during the current study Consent for publication : Not applicable Acknowledgments: Not applicable References : 1. Alnuqaydan AM. The dark side of beauty: an in-depth analysis of the health hazards and toxicological impact of synthetic cosmetics and personal care products. Frontiers in Public Health. 2024 Aug 26; 12:1439027. [PubMed] 2. Knuutila JS, Riihilä P, Karlsson A, Tukiainen M, Talve L, Nissinen L, Kähäri VM. Identification of metastatic primary cutaneous squamous cell carcinoma utilizing artificial intelligence analysis of whole slide images. Scientific reports. 2022 Jun 14;12(1):9876.[PubMed] 3. Lalmalani RM, Lim CX, Oh CC. Artificial intelligence in dermatopathology: a systematic review. Clinical and Experimental Dermatology. 2025 Feb;50(2):251-9. [PubMed] 4. Du‐Harpur X, Watt FM, Luscombe NM, Lynch MD. What is AI? Applications of artificial intelligence to dermatology. British Journal of Dermatology. 2020 Sep 1;183(3):423-30. [PubMed] 5. Braun SA, Schmidle P, Duschner N, Schaller J. Stand der Digitalisierung in der Dermatopathologie. Die Pathologie. 2025 Jan 3:1-6 [PubMed] 6. Peracca SB, Jackson GL, Lamkin RP, Mohr DC, Zhao M, Lachica O, Prentice JC, Grenga AM, Gifford A, Chapman JG, Weinstock MA. Implementing teledermatology for rural veterans: an evaluation using the RE-AIM framework. Telemedicine and e-Health. 2021 Feb 1;27(2):218-26. [PubMed] Information & Authors Information Version history V1 Version 1 18 April 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence dermatology quality healthcare resource-limited settings Authors Affiliations Najia Sadiq1 0009-0001-7796-3580 [email protected] Jinnah Sindh Medical University View all articles by this author Osaid Ahmed1 Jinnah Sindh Medical University View all articles by this author Tooba Ali 0000-0003-1867-943X Dow University of Health Sciences View all articles by this author Zainab Muhammad Hanif3 Shaheed Mohtarma Benazir Bhutto Medical College View all articles by this author Metrics & Citations Metrics Article Usage 192 views 113 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Najia Sadiq1, Osaid Ahmed1, Tooba Ali, et al. Will Artificial Intelligence be a Transformative Solution for Dermatological Care in Resource-Limited Settings?. Authorea . 18 April 2025. 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