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Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting.

Artificial Intelligence Versus Human Focus Group Rating of Facial Attractiveness.

Facial plastic surgery & aesthetic medicine
Many open-access artificial intelligence (AI)-based websites that rate facial attractiveness are available, but none have been compared with human focus group outcomes. To compare human and AI-based websites scoring of facial attractiveness of adul...

DeepAlienorNet: A deep learning model to extract clinical features from colour fundus photography in age-related macular degeneration.

Acta ophthalmologica
OBJECTIVE: This study aimed to develop a deep learning (DL) model, named 'DeepAlienorNet', to automatically extract clinical signs of age-related macular degeneration (AMD) from colour fundus photography (CFP).

AI-based diagnosis and phenotype - Genotype correlations in syndromic craniosynostoses.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Apert (AS), Crouzon (CS), Muenke (MS), Pfeiffer (PS), and Saethre Chotzen (SCS) are among the most frequently diagnosed syndromic craniosynostoses. The aims of this study were (1) to train an innovative model using artificial intelligence (AI)-based ...

Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography.

BMC medical informatics and decision making
BACKGROUND: The epiretinal membrane (ERM) is a common retinal disorder characterized by abnormal fibrocellular tissue at the vitreomacular interface. Most patients with ERM are asymptomatic at early stages. Therefore, screening for ERM will become in...

A Narrative Review: Opportunities and Challenges in Artificial Intelligence Skin Image Analyses Using Total Body Photography.

The Journal of investigative dermatology
Artificial intelligence (AI) algorithms for skin lesion classification have reported accuracy at par with and even outperformance of expert dermatologists in experimental settings. However, the majority of algorithms do not represent real-world clini...

Automated Prediction of Photographic Wound Assessment Tool in Chronic Wound Images.

Journal of medical systems
Many automated approaches have been proposed in literature to quantify clinically relevant wound features based on image processing analysis, aiming at removing human subjectivity and accelerate clinical practice. In this work we present a fully auto...

Segmentation and classification of skin burn images with artificial intelligence: Development of a mobile application.

Burns : journal of the International Society for Burn Injuries
AIM: This study was conducted to determine the segmentation, classification, object detection, and accuracy of skin burn images using artificial intelligence and a mobile application. With this study, individuals were able to determine the degree of ...

Artificial intelligence for oral squamous cell carcinoma detection based on oral photographs: A comprehensive literature review.

Cancer medicine
INTRODUCTION: Oral squamous cell carcinoma (OSCC) presents a significant global health challenge. The integration of artificial intelligence (AI) and computer vision holds promise for the early detection of OSCC through the analysis of digitized oral...