AIMC Topic: Melanoma

Clear Filters Showing 61 to 70 of 335 articles

Artificial intelligence-assisted metastasis and prognosis model for patients with nodular melanoma.

PloS one
OBJECTIVE: The objective of this study was to identify the risk factors that influence metastasis and prognosis in patients with nodular melanoma (NM), as well as to develop and validate a prognostic model using artificial intelligence (AI) algorithm...

Adaptive neighborhood triplet loss: enhanced segmentation of dermoscopy datasets by mining pixel information.

International journal of computer assisted radiology and surgery
PURPOSE: The integration of deep learning in image segmentation technology markedly improves the automation capabilities of medical diagnostic systems, reducing the dependence on the clinical expertise of medical professionals. However, the accuracy ...

Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

PLoS computational biology
Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morphological changes during metastatic transformation. While pivotal, the role of specific mutations in dictating these changes still needs to be fully eluci...

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...

Deep learning algorithms for melanoma detection using dermoscopic images: A systematic review and meta-analysis.

Artificial intelligence in medicine
BACKGROUND: Melanoma is a serious risk to human health and early identification is vital for treatment success. Deep learning (DL) has the potential to detect cancer using imaging technologies and many studies provide evidence that DL algorithms can ...

Asymmetric lesion detection with geometric patterns and CNN-SVM classification.

Computers in biology and medicine
In dermoscopic images, which allow visualization of surface skin structures not visible to the naked eye, lesion shape offers vital insights into skin diseases. In clinically practiced methods, asymmetric lesion shape is one of the criteria for diagn...

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...

Artificial intelligence and skin melanoma.

Clinics in dermatology
Melanoma is the deadliest skin cancer, presenting typically with changing pigmented areas and usually treated with surgical removal. As benign cutaneous pigmented lesions are very common in all populations, it can be challenging to identify which are...