Skin care Recommender System using Artificial intelligence and Medical techniques

Project Title

Skin care Recommender System using Artificial intelligence and Medical techniques

Project Area of Specialization Artificial IntelligenceProject Summary

Since cell phones have become an intrinsic part of our daily lives, why not use them to save our time, money, and effort in a new way. The Skincare Recommender system will be Artificial intelligence (AI) Android-based application that will automate the whole process of diagnosis skin anomalies by capturing the image of infective part of the skin, process this image, and then predict and diagnose the disease in an efficient way through mobile phones. AI Android application will work as a virtual doctor. This app will help users to the prevention of respective diseases and also helps in treatment. This way Skincare Recommender system (SCR system) will provide all skincare handling services that will be precise, accurate, and with the required prevention and treatment to save the precious lives of the individuals.

Project Objectives

Primary Objective:
1. Mobile platform for Recommender System
2. Instant care for skin diseases
3. Review & Treatment for diseases on a daily base
Academic Objective:
1. Development of an Android based application for end-user
2. Using modern research fields
Application/End-user Objective:
1. To facilitate the end-users of the application in terms of the SCR system.
 

Project Implementation Method

Deep learning approaches for Anomaly detection are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning & convolutional neural network approaches for the classification & recognition of image.

First, we review the current deep learning architectures and CNN algorithm used for training to discover auseful pattern in the digital representation of data. Next, the performance, speed, and accuracy approaches are summarized and discussed. Furthermore, this model provides an effective treatment for anomalies.

The following strategy is used for developing SCR system application:
• Collect real-time dataset.
• prepare dataset and build and train a model using ML and        Deep Learning algorithms.
• Test the Model and make some predictions.
• Take sample input image and Test the requirement’s accuracy of Model.
 

Benefits of the Project

Since cell phones have become an integral part of our daily lives, why not save our time, money, and effort
in a new way. The traditional method of diagnosing skin diseases is based on going to a dermatologist.
Users/patients will waste appointment time and then wait for their turn. When people have to stand in long
lines to meet, people get angry which can lead to Irregular confiscation. Sometimes people are reluctant to
go to the doctor for some reason, which aggravates their disease, and then worsens.
So, we should have a system that can get rid of all the problems that a specialist doctor can give without
any trouble.
 

Technical Details of Final Deliverable

In the final deliverable, a complete software app is built and it is then it will use for people.

Final Deliverable of the Project Software SystemCore Industry MedicalOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	67500
laptop/machine	Equipment	1	60000	60000
doctor appointment fee	Miscellaneous	5	1500	7500