AI Medical Compendium Journal:
Melanoma research

Showing 1 to 4 of 4 articles

Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.

Melanoma research
Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer rec...

The potential of using artificial intelligence to improve skin cancer diagnoses in Hawai'i's multiethnic population.

Melanoma research
Skin cancer remains the most commonly diagnosed cancer in the USA with more than 1 million new cases each year. Melanomas account for about 1% of all skin cancers and most skin cancer deaths. Multiethnic individuals whose skin is pigmented underestim...

Machine learning for the identification of decision boundaries during the transition from radial to vertical growth phase superficial spreading melanomas.

Melanoma research
The objective of this study was to compute threshold values for the diameter of superficial spreading melanomas (SSMs) at which the radial growth phase (RGP) evolves into an invasive vertical growth phase (VGP). We examined reports from 1995 to 2019 ...

Novel strategy for applying hierarchical density-based spatial clustering of applications with noise towards spectroscopic analysis and detection of melanocytic lesions.

Melanoma research
Advancements in dermoscopy techniques have elucidated identifiable characteristics of melanoma which revolve around the asymmetrical constitution of melanocytic lesions consequent of unfettered proliferative growth as a malignant lesion. This study e...