Data for: Quantification of randomness (Entropy) as a clinical tool to assess the severity of skin disease
Description of this data
Quantitative analysis of the skin is a new, quick, and very efficient method to quantify various skin changes like performing health assessments, determine skin conditions, and evaluating how skin responds to assigned treatment course(s). The quantitative analysis allows to produce universal measures of different skin conditions that would be more accurate and non-biased. It was theoreticized that healthy skin is more structured compared to the affected skin which exhibits more alterations due to neoplastic, inflammatory, or traumatic processes.
The dermatology clinic database of deidentified dermatoscopic images of the skin affected by psoriasis and adjacent clinically intact skin were used for the current analysis. All images were captured by Visioscope PC 35 camera device (Courage + Khazaka, Germany ). All images (raw data) were transferred into specially coded and developed proprietary software which enables its users to calculate entropy values for healthy and non-healthy skin.
Blank paper (baseline with minimum randomness), gridded paper (interpreted as the simplified model of skin), and chaotic patterns (interpreted as the skin affected by lesions) were used as reference entropy values. The Mann-Whitney U method was used to determine the statistical significance of gathered data. The entropy values for normal unaffected skin exhibited normal distribution with mean of 2.56 with 95% confidence interval of [2.36, 2.75]. The skin affected by psoriasis exhibited normal distribution with mean of 3.30 with 95% confidence of [2.93, 3.66].
The healthy skin has a lower entropy values compared to the entropy values of skin affected by psoriasis. That is because the healthy skin appears to have more uniformed patterns in its structure, while the skin affected by psoriasis exhibits more random features due to traumatic processes and inflammation.
The current technique of implying a mathematical algorithm to calculate the Maximum entropy shows promising results because physicians would be able to use universal measures to access skin conditions with minimal sources of error.
Experiment data files
This data is associated with the following publication:
Cite this dataset
Breslavets, Alina (2019), “Data for: Quantification of randomness (Entropy) as a clinical tool to assess the severity of skin disease”, Mendeley Data, v1 http://dx.doi.org/10.17632/cr4vwzrd8k.1
The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.