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Skin Cancer

Skin Cancer

Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
Basal Cell Carcinoma (BCC): BCC is the most common type of skin cancer, accounting for about 80% of cases. It typically develops in...

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Related Experiment Video

Updated: Nov 22, 2025

High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

High-throughput Imaging and Analysis Workflow for Evaluating Skin Cell Phenotypes and Proliferation States in Tissue Samples

Published on: October 31, 2025

An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management.

Ilias Maglogiannis¹, Georgia Kontogianni^2,3,4, Olga Papadodima³

¹Department of Digital Systems, University of Piraeus, 126 Grigoriou Lambraki, 18534, Piraeus, Greece. imaglo@unipi.gr.

Journal of Medical Systems

|January 6, 2021

Summary

This summary is machine-generated.

This study introduces a new platform to integrate diverse patient data for better skin cancer management. It enables personalized medicine by combining omics, imaging, and clinical information for early melanoma detection.

Keywords:

Clinical decision support tools Composite biomarkers Dermoscopy Melanoma Next generation sequencing

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Area of Science:

Biomedical Informatics
Oncology
Dermatology

Background:

Electronic Health Record (EHR) systems enhance healthcare by integrating data and decision support.
Current EHRs often lack the capacity to integrate complex, multidimensional patient data.

Purpose of the Study:

To present a modular, distributed platform for integrating heterogeneous, multidimensional data (omics, histology, clinical) for skin cancer patient management.
To expand current EHR systems with a layered analytical framework for comprehensive patient data integration.

Main Methods:

Developed a platform capable of integrating high-volume molecular omics data, imaging data, and clinical observations.
Implemented a layered analytical framework as an extension of existing EHR systems.
Conducted a case study in dermatology focusing on melanoma detection and characterization.

Main Results:

Successfully integrated multilayered information for multi-angled portrayal and management of skin cancer patients.
Demonstrated the platform's ability to combine omics, imaging, and clinical data for melanoma analysis.
Addressed technical implementation challenges and provided an initial system evaluation.

Conclusions:

The proposed platform facilitates the integration of complex data for improved skin cancer patient management.
This architecture aims to reduce barriers to personalized therapeutic approaches and advance precision medicine in dermatology.
The study provides insights into the technical aspects and initial performance of the integrated system.