SMART DERMA: MOBILE APPLICATION FOR SKIN-DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK

Skin disease is an emergent public health problem worldwide, particularly in developing countries wherehealthcare access is limited. To address these challenges, the rapid advancement in Artificial Intelligence (AI) andMachine Learning (ML) technologies has introduced new opportunities to improve healthcare access anddiagnostic potential. This study of Smart Derma: Mobile Application for Skin-Disease Detection UsingConvolutional Neural Network (CNN) aims to address the growing need for accessible and reliable tools indermatological self-assessment. This is a mobile application for skin disease detection using Convolutional NeuralNetwork that will assist the users for detecting possible skin diseases through image-based analysis. It wasconducted as a developmental approach at Gat Andres Bonifacio Memorial Medical Center and Justice Jose AbadSantos General Hospital and was assessed by professionals, patients, and students to evaluate its usability andreliability. However, Smart Derma mobile application is not a substitute for dermatologists but an adjunct, initialscreening device to identify potential skin conditions. The study yielded both favorable and unfavorable outcomesthat will help students, patients, healthcare providers and future proponents while further validation andimprovement remain essential in continuing these studies.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-07
DOI
https://doi.org/10.5281/zenodo.17283005
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00
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article

SMART DERMA: MOBILE APPLICATION FOR SKIN-DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK

Zenodo (CERN European Organization for Nuclear Research)
Soil Moisture and Remote Sensing
article

SMART DERMA: MOBILE APPLICATION FOR SKIN-DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK

article en

Abstract

Skin disease is an emergent public health problem worldwide, particularly in developing countries wherehealthcare access is limited. To address these challenges, the rapid advancement in Artificial Intelligence (AI) andMachine Learning (ML) technologies has introduced new opportunities to improve healthcare access anddiagnostic potential. This study of Smart Derma: Mobile Application for Skin-Disease Detection UsingConvolutional Neural Network (CNN) aims to address the growing need for accessible and reliable tools indermatological self-assessment. This is a mobile application for skin disease detection using Convolutional NeuralNetwork that will assist the users for detecting possible skin diseases through image-based analysis. It wasconducted as a developmental approach at Gat Andres Bonifacio Memorial Medical Center and Justice Jose AbadSantos General Hospital and was assessed by professionals, patients, and students to evaluate its usability andreliability. However, Smart Derma mobile application is not a substitute for dermatologists but an adjunct, initialscreening device to identify potential skin conditions. The study yielded both favorable and unfavorable outcomesthat will help students, patients, healthcare providers and future proponents while further validation andimprovement remain essential in continuing these studies.

Zenodo (CERN European Organization for Nuclear Research)
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Soil Moisture and Remote Sensing
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SMART DERMA: MOBILE APPLICATION FOR SKIN-DISEASE DETECTION USING CONVOLUTIONAL NEURAL NETWORK · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS