AIMC Topic: Skin Diseases

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Classifying real-world macroscopic images in the primary-secondary care interface using transfer learning: implications for development of artificial intelligence solutions using nondermoscopic images.

Clinical and experimental dermatology
BACKGROUND: The application of deep learning (DL) to diagnostic dermatology has been the subject of numerous studies, with some reporting skin lesion classification performance on curated datasets comparable to that of experienced dermatologists. Mos...

ChatGPT versus clinician: challenging the diagnostic capabilities of artificial intelligence in dermatology.

Clinical and experimental dermatology
BACKGROUND: ChatGPT is an online language-based platform designed to answer questions in a human-like way, using deep learning -technology.

Current State of Dermatology Mobile Applications With Artificial Intelligence Features.

JAMA dermatology
IMPORTANCE: With advancements in mobile technology and artificial intelligence (AI) methods, there has been a substantial surge in the availability of direct-to-consumer mobile applications (apps) claiming to aid in the assessment and management of d...

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The British journal of dermatology
The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detection to large language models like ChatGPT that can answer generalist or specialist questions about sk...

Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Hair and scalp disorders present a significant challenge in dermatology due to their clinical diversity and overlapping symptoms, often leading to misdiagnoses. Traditional diagnostic methods rely heavily on clinical expertise and are lim...

Robust Visual Identification of Under-resourced Dermatological Diagnoses with Classifier-Steered Background Masking.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Collecting images of rare dermatological diseases for machine learning detection applications is a costly, laborious task. It is difficult to collect enough images of these diagnoses to avoid the risk of low accuracy "in the wild". One of the sources...

Segmentation and classification of skin lesions using hybrid deep learning method in the Internet of Medical Things.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
INTRODUCTION: Particularly within the Internet of Medical Things (IoMT) context, skin lesion analysis is critical for precise diagnosis. To improve the accuracy and efficiency of skin lesion analysis, CAD systems play a crucial role. To segment and c...