AIMC Topic: Uveal Neoplasms

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Automatic classification of uveal melanoma response patterns following ruthenium-106 plaque brachytherapy using ultrasound images and deep convolutional neural network.

Scientific reports
Following uveal melanoma (UM) affected treatment using ruthenium-106 brachytherapy, tumor thickness patterns fall into one of four categories: decrease (regression), increase (recurrence), stop (stable), or other, which are assessed in follow-up A-mo...

Artificial intelligence and different image modalities in uveal melanoma diagnosis and prognosis: A narrative review.

Photodiagnosis and photodynamic therapy
BACKGROUND: The most widespread primary intraocular tumor in adults is called uveal melanoma (UM), if detected early enough, it can be curable. Various methods are available to treat UM, but the most commonly used and effective approach is plaque rad...

Artificial intelligence in the diagnosis of uveal melanoma: advances and applications.

Experimental biology and medicine (Maywood, N.J.)
Advancements in machine learning and deep learning have the potential to revolutionize the diagnosis of melanocytic choroidal tumors, including uveal melanoma, a potentially life-threatening eye cancer. Traditional machine learning methods rely heavi...

Artificial intelligence with ChatGPT 4: a large language model in support of ocular oncology cases.

International ophthalmology
PURPOSE: To evaluate ChatGPT's ability to analyze comprehensive case descriptions of patients with uveal melanoma and provide recommendations for the most appropriate management.

Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma.

Journal of translational medicine
BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), distant metastasis remains the leading cause of death in patients. Monitoring, staging, and treatment of metastatic disease have not yet reached conse...

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Cancer science
Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning metho...

Colour fusion effect on deep learning classification of uveal melanoma.

Eye (London, England)
BACKGROUND: Reliable differentiation of uveal melanoma and choroidal nevi is crucial to guide appropriate treatment, preventing unnecessary procedures for benign lesions and ensuring timely treatment for potentially malignant cases. The purpose of th...

Automated segmentation for early detection of uveal melanoma.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: Uveal melanoma is the most common intraocular malignancy in adults. Current screening and triaging methods for melanocytic choroidal tumours face inherent limitations, particularly in regions with limited access to specialized ocular oncol...

Integrating single-cell analysis and machine learning to create glycosylation-based gene signature for prognostic prediction of uveal melanoma.

Frontiers in endocrinology
BACKGROUND: Increasing evidence suggests a correlation between glycosylation and the onset of cancer. However, the clinical relevance of glycosylation-related genes (GRGs) in uveal melanoma (UM) is yet to be fully understood. This study aimed to shed...