AIMC Topic: Photography

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Enhancing Diagnosis of Psoriasis and Inflammatory Skin Diseases: A Spatially Aligned Multimodal Model Integrating Clinical and Dermoscopic Images.

The Journal of investigative dermatology
Psoriasis is a chronic inflammatory disease with significant physical and psychological impacts. To overcome the limitations of single-modality artificial intelligence models in diagnosing inflammatory skin diseases, we propose a multimodal framework...

Can off-the-shelf visual large language models detect and diagnose ocular diseases from retinal photographs?

BMJ open ophthalmology
BACKGROUND: The advent of generative artificial intelligence has led to the emergence of multiple vision large language models (VLLMs). This study aimed to evaluate the capabilities of commonly available VLLMs, such as OpenAI's GPT-4V and Google's Ge...

Acceptability, applicability, and cost-utility of artificial-intelligence-powered low-cost portable fundus camera for diabetic retinopathy screening in primary health care settings.

Diabetes research and clinical practice
AIMS: To evaluate the acceptability, applicability, and cost-utility of AI-powered portable fundus cameras for diabetic retinopathy (DR) screening in Hong Kong, providing a viable alternative screening solution for resource-limited areas.

Comparative analysis of deep learning architectures for thyroid eye disease detection using facial photographs.

BMC ophthalmology
PURPOSE: To compare two artificial intelligence (AI) models, residual neural networks ResNet-50 and ResNet-101, for screening thyroid eye disease (TED) using frontal face photographs, and to test these models under clinical conditions.

Automated detection of retinal artery occlusion in fundus photography via self-supervised deep learning and multimodal interpretability using a multimodal AI chatbot.

Medical & biological engineering & computing
Retinal artery occlusion (RAO) is a sight-threatening condition that requires prompt diagnosis to prevent irreversible vision loss. This study presents an innovative AI-driven approach for RAO detection from fundus images, marking the first applicati...

The current state of forensic imaging - perspectives.

International journal of legal medicine
This fourth part of the review of the current state of forensic imaging describes the future potential influence of artificial intelligence in forensic imaging. In addition to this important point, training in forensic imaging is discussed in detail,...

Addressing underestimation and explanation of retinal fundus photo-based cardiovascular disease risk score: Algorithm development and validation.

Computers in biology and medicine
OBJECTIVE: To resolve the underestimation problem and investigate the mechanism of the AI model which employed to predict cardiovascular disease (CVD) risk scores from retinal fundus photos.

Point-of-interest recommender model using geo-tagged photos in accordance with imperialist Fuzzy C-means clustering.

PloS one
Although recommender systems (RSs) strive to provide recommendations based on individuals' histories and preferences, most recommendations made by these systems do not utilize location and time-based information. This paper presents a travel recommen...

Large-scale benchmarking and boosting transfer learning for medical image analysis.

Medical image analysis
Transfer learning, particularly fine-tuning models pretrained on photographic images to medical images, has proven indispensable for medical image analysis. There are numerous models with distinct architectures pretrained on various datasets using di...

An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs.

Nutrients
: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimatin...