Skin Friend

Skin Disease Diagnosis in the Palm of Your Hand.

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Introduction

Meet Skin Friend, the app which will save thousands of lives. At Skin Friend, we aim to democratize and accelerate healthcare, by providing free cancer detection resources, in the palm of your hand. One in every three cancers is skin cancer. In the United States, the country with the highest number of cases (by a long shot), one in every five people gets skin cancer. That is 9,500 cases daily! This year, 196,060 Americans will be diagnosed with skin cancer, out of whom 6,850 will die. Throughout the entire world, 2-3 million people will be diagnosed with skin cancer and many will die because they aren’t diagnosed and don’t get help. But it doesn't have to be this way. So far, we have only looked at people who are able to see doctors. 46 million Americans lack health care resources and are unable to access frequent medical checkups. That is 46 million people and counting under the radar! All diagnosed cases come from those who are able to meet medical professionals regularly, but what about people who do not have these resources? They won’t find out they have a disease and they cannot get the treatment they need as a result. That’s where we come in: Skin Friend builds bridges towards democratizing healthcare. Regardless of background, income, and situation, anyone can diagnose critical diseases easily, affordably, and rapidly. Considering the increasing severity of skin cancer, it is more important than ever to prevent deaths from this otherwise easily treatable condition. If skin cancer is diagnosed early, there is a 99% survival rate, and Skin Friend provides exactly that: rapid and convenient diagnosis. No longer do you have to wonder whether you should see a doctor or worry about paying expenses to visit the hospital for the random dark spot on your skin: simply scan your problem Skin Friend, and receive a diagnosis in seconds. For free. Skin Friend allows the user to diagnose their skin problems early on, so if it is skin cancer, they will still have a high survival rate and get the help they need ASAP.

Inspiration

The Skin Friends team was inspired by personal experiences, whether it was sheer laziness to visit the doctors office when something minor happened (such as irregularities in the skin), and the shock that came with learning how many people are unable to regularly visit doctors. Our team acknowledges the privilege we have by being able to afford healthcare, so we decided to use this privilege to help others who lack basic necessities, especially healthcare. Health care is a basic human need, and unfortunately, our world leaders have failed to provide access to this, so why not DIY it?

What it does

Skin Friend may be a simple app, but it packs quite the punch. Singlehandedly, Skin Friend democratizes and accelerates the health care system by providing easy and free skin cancer detection! Here at Skin Friend, we pride ourselves on our simplicity and ease of use. Skin Friend only requires a working phone with a camera (something which almost everyone has, 45% of world population including elderly and young kids), and a $5 zoom attachment (if you're feeling fancy). The introductory page features an intuitive step-by-step guide on the steps that need to be taken to use our app. Users are then given three options (in flowchart form for the suggested order). The first and most important feature is the diagnosis feature. Users are prompted to take a picture of their problematic skin area in the app. After taking the picture, users are quickly diagnosed with their skin-related issue. The other pages include an “information” page and a “contact” page, meant to provide easy access to doctors and hospitals if needed, and great customer service. Skin Friend does not require fancy images like an MRI scan, because a phone camera does the job pretty well! Make sure to check out our UI mockups to see what our app will look like once it is launched!

How we built it

We selected the HAM10000 dataset for our project. After extensive coding and testing, we used a Convolutional Neural Network in TensorFlow to create a custom model with high accuracy for diagnosing skin cancer. Unfortunately, our ML engineers lacked a GPU, so we used Google Colab, which allowed us to test and edit much faster. We used pandas and numpy for reading and storing images. We also used scikit-learn for a few functions such as train test splitting. We used transfer learning with Xception as the base and added model layers on top. Our preprocessing and model training was all done in the cloud and we collaborated through Google Meet to discuss things live. This hackathon was also the first time our frontend developer programmed a full web app, which made SET hacks a front-to-end learning experience! We also used Canva to design our UI and screen recording software to record demo videos.

Challenges we ran into

There were multiple challenges, such as the model's long training time (taking hours at best) which reduced how much we could tweak and fiddle with parameters to find the best accuracy. We worked around them by doing most of the guesswork and research at the beginning, before running the program. Other challenges included the preprocessing, which took a lot of googling to fully materialize and it took a while due to our limited processing power at home. Furthermore, our UI developer was almost completely new to frontend development (props to our frontend developer for learning everything in under 48 hours)! The 12 hour time zone difference between our members was another huge challenge, which involved a lot of early mornings and late nights to overcome. At Skin Friend, time was our biggest challenge, which we overcame by clearly outlining tasks to prevent overlap, optimizing run time so we could work on background tasks, and a LOT of research.

Accomplishments that we are proud of

The Skin Friends team is proud of every aspect of our app! We believe that our cause (democratizing and accelerating healthcare) is very important. We believe that our app is a great first step in improving the healthcare system, and we hope to further develop it (and inspire others to improve healthcare along the way). We are proud of overcoming many obstacles, as highlighted in the above section. We went through many mentally taxing periods, whether it was pulling all nighters to overcome the time zone difference, recording and re-recording our video until it was just perfect, and learning web development from front-to-end, all in 48 hours, and we're glad we didn't give up (or pull out of this hackathon to apply for a later one). On a more technical note, we are proud of the high accuracy our Convolutional Neural Network achieved in such a short amount of time! We are also proud of the intuitive UI of our app, and, on a less serious note, we really like our tagline!

While Skin Friends is an app we are proud of, we hope to perpetually improve it to make everyone proud! We admit it, our UI could be improved, our model could be more accurate, and we could definitely use more marketing, and we are proud of the fact that we will continue to work on this app until it is perfect, and maybe detect a few more diseases along the way!

What we learned

Bridge Hacks was a front-to-end learning experience! 1/2 of the team had little to no experience with hackathons, and Bridge Hacks was definitely a great gateway into hacking! As mentioned countless times, this was a front-to-end learning experience for our UI developer, and one of our ML hackers was also a beginner! Each obstacle we overcame was a new learning opportunity. The extensive research done regarding UI and which ML model we should use gave us a much better grasp of key concepts in both fields. On a less important note, we definitely got much better at surviving on three hours of sleep.

What's next for Skin Friend

Currently, Skin Friends has the potential to save millions of people from skin cancer and bridge the gap of healthcare access. We’re all aware of inadequacies in the American expensive healthcare system and in other less fortunate countries and in rural villages, few lack basic access to doctors. Skin Friend has a positive future outlook, including detection of other diseases which can be seen externally, including (but definitely not limited to) various eye diseases. Through Skin Friends, we will code our way to a better and more accessible healthcare system. As mentioned above, we would like to improve on every aspect of our app! While the functionality is there, we don't believe in the "If it ain't broke then don't fix it" method!

Thanks for reading, and happy skincare!

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