AIMC Topic: Photography
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Diagnosis and Screening of Velocardiofacial Syndrome by Evaluating Facial Photographs Using a Deep Learning-Based Algorithm.
Plastic and reconstructive surgery
Oct 1, 2024
BACKGROUND: Early detection of rare genetic diseases, including velocardiofacial syndrome (VCFS), is essential for patient well-being. However, the rarity of these diseases and limited clinical experience of physicians make diagnosis challenging. Dee...
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.
The lancet. Healthy longevity
Sep 30, 2024
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
SCAWA scales: A new digital tool for wrinkles clinical grading based on AI.
International journal of cosmetic science
Sep 29, 2024
OBJECTIVE: Clinical assessment of wrinkle depth is essential for efficacy evaluations of anti-ageing products. Standardized photographic scales, representative of different wrinkle depths are often used by experts to assign subjects reliable grades. ...
Computer Vision Identification of Trachomatous Inflammation-Follicular Using Deep Learning.
Cornea
Sep 20, 2024
PURPOSE: Trachoma surveys are used to estimate the prevalence of trachomatous inflammation-follicular (TF) to guide mass antibiotic distribution. These surveys currently rely on human graders, introducing a significant resource burden and potential f...
Evaluation of AI-enhanced non-mydriatic fundus photography for diabetic retinopathy screening.
Photodiagnosis and photodynamic therapy
Sep 7, 2024
OBJECTIVE: To assess the feasibility of using non-mydriatic fundus photography in conjunction with an artificial intelligence (AI) reading platform for large-scale screening of diabetic retinopathy (DR).
Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera.
BMJ open
Sep 5, 2024
OBJECTIVES: Despite global research on early detection of age-related macular degeneration (AMD), not enough is being done for large-scale screening. Automated analysis of retinal images captured via smartphone presents a potential solution; however,...
Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.
Journal of biomedical informatics
Sep 5, 2024
OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in autom...
Comparison of deep learning models to detect crossbites on 2D intraoral photographs.
Head & face medicine
Sep 2, 2024
BACKGROUND: To support dentists with limited experience, this study trained and compared six convolutional neural networks to detect crossbites and classify non-crossbite, frontal, and lateral crossbites using 2D intraoral photographs.
Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones.
Heart (British Cardiac Society)
Aug 14, 2024
BACKGROUND: Researchers have developed machine learning-based ECG diagnostic algorithms that match or even surpass cardiologist level of performance. However, most of them cannot be used in real-world, as older generation ECG machines do not permit i...
Novel use of deep neural networks on photographic identification of epaulette sharks (Hemiscyllium ocellatum) across life stages.
Journal of fish biology
Aug 10, 2024
Photographic identification (photo ID) is an established method that is used to count animals and track individuals' movements. This method performs well with some species of elasmobranchs (i.e., sharks, skates, and rays) where individuals have disti...
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