As a part of my internship at Ismile Technologies, I am working on an Oncology project – something that I have wanted to work on for a very long time. I’m immensely grateful for this excellent opportunity to lead and work with a very talented team for materializing this project.The inspiration for our Cancer Detection Project stems from the fact that countless people end up losing their energy, money and even their lives just because they were not able to detect and treat cancer on time. Consequently, this project is extremely relevant to people and healthcare departments worldwide.The project enables users to click and securely upload images- of growths, lumps or other irregularities that might be a symptom of Skin Cancer, to our app and find out whether it is cancerous. They can also learn about the next steps that need to be taken. The user data will be kept entirely confidential. We are working with Skin cancer since it has the most visible symptoms. The app will also require certain contextual input (symptoms, mood, etc.) from the users to enhance the accuracy of prediction further.So far in this journey, we have collected and preprocessed the dataset, which closely resembles the images users might click using their mobiles to ensure accuracy. After substantial research and discussions, we have a comprehensive idea for our data models and are now in the training and testing stage of the data models.In the future, we look forward to achieving an even higher accuracy rate for our models, their successful deployment, incorporating a recommendation system for hospitals and making the app extremely user-friendly— Palak MunshiAs a part of my internship at Ismile Technologies, I am working on an Oncology project – something that I have wanted to work on for a very long time. I’m immensely grateful for this excellent opportunity to lead and work with a very talented team for materializing this project.The inspiration for our Cancer Detection Project stems from the fact that countless people end up losing their energy, money and even their lives just because they were not able to detect and treat cancer on time. Consequently, this project is extremely relevant to people and healthcare departments worldwide.The project enables users to click and securely upload images- of growths, lumps or other irregularities that might be a symptom of Skin Cancer, to our app and find out whether it is cancerous. They can also learn about the next steps that need to be taken. The user data will be kept entirely confidential. We are working with Skin cancer since it has the most visible symptoms. The app will also require certain contextual input (symptoms, mood, etc.) from the users to enhance the accuracy of prediction further.So far in this journey, we have collected and preprocessed the dataset, which closely resembles the images users might click using their mobiles to ensure accuracy. After substantial research and discussions, we have a comprehensive idea for our data models and are now in the training and testing stage of the data models.In the future, we look forward to achieving an even higher accuracy rate for our models, their successful deployment, incorporating a recommendation system for hospitals and making the app extremely user-friendly— Palak Munshi