The Therapeutic Applications of Machine Learning in Atopic Dermatitis: A Scoping Review

McMullen, Eric P; Syed, Saad; Espiritu, Kristopher D; Grewal, Rajan; Elder, Geoffrey A; Morita, Plinio Pelegrini; Drucker, Aaron M.

doi:10.1177/12034754231168846

Cited by 2 publications

(1 citation statement)

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“…Similar to diagnostic tasks with psoriasis, many researchers have explored using machine learning algorithms in dermatitis ( 48 ), ranging from image-based algorithms ( 49 ) to electronic health record text-based algorithms ( 50 ). Aside from determining diagnoses, researchers have developed proof-of-concept algorithms using self-reported eczema flare scores, patient demographics and treatment history to predict atopic dermatitis severity, resulting in a biologically interpretable model that focuses on patient’s responsiveness to treatment ( 51 ).…”

Section: Applications Of Ai In Dermatologymentioning

confidence: 99%

Principles, applications, and future of artificial intelligence in dermatology

Omiye,

Gui,

Daneshjou

et al. 2023

Front. Med.

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This paper provides an overview of artificial-intelligence (AI), as applied to dermatology. We focus our discussion on methodology, AI applications for various skin diseases, limitations, and future opportunities. We review how the current image-based models are being implemented in dermatology across disease subsets, and highlight the challenges facing widespread adoption. Additionally, we discuss how the future of AI in dermatology might evolve and the emerging paradigm of large language, and multi-modal models to emphasize the importance of developing responsible, fair, and equitable models in dermatology.

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Section: Applications Of Ai In Dermatologymentioning

confidence: 99%

Principles, applications, and future of artificial intelligence in dermatology

Omiye,

Gui,

Daneshjou

et al. 2023

Front. Med.

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Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases

Li Pomi,

Papa,

Borgia

et al. 2024

Life

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Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses. Advancements in the field of artificial intelligence (AI) have shown promise in enhancing the diagnosis, management, and assessment of immuno-correlated dermatological pathologies. This intersection of dermatology and immunology plays a pivotal role in comprehending and addressing complex skin disorders with immune system involvement. The paper explores the knowledge known so far and the evolution and achievements of AI in diagnosis; discusses segmentation and the classification of medical images; and reviews existing challenges, in immunological-related skin diseases. From our review, the role of AI has emerged, especially in the analysis of images for both diagnostic and severity assessment purposes. Furthermore, the possibility of predicting patients’ response to therapies is emerging, in order to create tailored therapies.

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The Therapeutic Applications of Machine Learning in Atopic Dermatitis: A Scoping Review

Cited by 2 publications

References 0 publications

Principles, applications, and future of artificial intelligence in dermatology

Principles, applications, and future of artificial intelligence in dermatology

Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases

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