AIMC Topic: Skin Pigmentation

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Skin Phototype Classification with Machine Learning Based on Broadband Optical Measurements.

Sensors (Basel, Switzerland)
The Fitzpatrick Skin Phototype Classification (FSPC) scale is widely used to categorize skin types but has limitations such as the underrepresentation of darker skin phototypes, low classification resolution, and subjectivity. These limitations may c...

Skin Cancer Detection in Diverse Skin Tones by Machine Learning Combining Audio and Visual Convolutional Neural Networks.

Oncology
INTRODUCTION: Skin cancer (SC) is common in fair skin (FS) at a 1:5 lifetime incidence for nonmelanoma skin cancer. In order to assist clinicians' decisions, a risk intervention technology was developed, which combines a dual-mode machine learning of...

Impact of Digital Advertising Policy on Harmful Product Promotion: Natural Language Processing Analysis of Skin-Lightening Ads.

American journal of preventive medicine
INTRODUCTION: Starting June 30, 2022, Google implemented its revised Inappropriate Content Advertising Policy, targeting discriminatory skin-lightening ads that suggest superiority of certain skin shades. This study evaluates the ad content changes f...

Spectrum-based deep learning framework for dermatological pigment analysis and simulation.

Computers in biology and medicine
BACKGROUND: Deep learning in dermatology presents promising tools for automated diagnosis but faces challenges, including labor-intensive ground truth preparation and a primary focus on visually identifiable features. Spectrum-based approaches offer ...

Validity of facial skin analysis pore detection: A comparative analysis.

Journal of cosmetic dermatology
BACKGROUND: Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard"...

Artificial intelligence in dermatology: advancements and challenges in skin of color.

International journal of dermatology
Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human-like problem-solving and decision-making. AI programs have recently acquired widespread popularity in the field of dermatology through the applicati...

Deep learning-aided decision support for diagnosis of skin disease across skin tones.

Nature medicine
Although advances in deep learning systems for image-based medical diagnosis demonstrate their potential to augment clinical decision-making, the effectiveness of physician-machine partnerships remains an open question, in part because physicians and...

Understanding skin color bias in deep learning-based skin lesion segmentation.

Computer methods and programs in biomedicine
BACKGROUND: The field of dermatological image analysis using deep neural networks includes the semantic segmentation of skin lesions, pivotal for lesion analysis, pathology inference, and diagnoses. While biases in neural network-based dermatoscopic ...

Remote Blood Oxygen Estimation From Videos Using Neural Networks.

IEEE journal of biomedical and health informatics
Peripheral blood oxygen saturation (SpO ) is an essential indicator of respiratory functionality and received increasing attention during the COVID-19 pandemic. Clinical findings show that COVID-19 patients can have significantly low SpO before any ...