Emily Jones, Jakob Melendez, Ashish Satyavarapu, Shruthi Krishnapuram, and James Nguyen
In many cases, a person's risk of developing cancer is linked to their genetic makeup. Overtime, researchers have made significant progress in identifying specific genetic mutations that increase the risk of developing certain types of cancer. Identifying patients who may be at risk, however, is a complicated and error-prone process. Physicians typically use a convulted series of questions to determine if a patient should be screened for hereditary cancer. This process can be challenging for both patients and physicians and may result in patients who need to be screened being missed. In response to this issue, our team proposes the development of a web and mobile application that can simplify the screening process by presenting the questions one after another in a user friendly interface making it more accessible to patients and physicians. Our aim is to improve the accuracy of patient outcomes and reduce the number of missed diagnoses.
The improvement of cancer screening for hereditary diseases is the collaboration between healthcare and computer science. This entails using technology and software to enhance the accuracy and efficiency of the process. Professionals in computer science create digital tools and applications to support healthcare professionals in their decision-making. These tools include decision trees, algorithms, and other aids for patient screening and diagnosis. The digital screening process proposed is a part of this area of computer science. It utilizes technology to create a more efficient and accurate screening process while giving real-time feedback to healthcare professionals. This feedback highlights areas of concern and decreases the possibility of errors or missed information.
SurveyJS was used to build the two surveys, PersonalHx and FamilyHx, in order to take the complex process mentioned in the Background, pertaining to the decision trees and convert them into an easy to use web application. The raw json files for each survey, showing how extensive they are, is located in the surveys_raw folder in this repository.
To locally access this web application clone this repository in a desired directory on your computer.
git clone https://github.com/jakobmelendez/SeniorProjectWebsite.git
Open up the cloned repository in your desired IDE, for instance, Visual Studio Code.
Once in your IDE, navigate to the command line and be sure that you are currently in the cloned repository directory. From here you can run the following command to start the web application locally.
npm start
After running this command the web application will open in your default browser and will be able to be used.
To access the website in your browser, click the link presented in the "About" section on this repository page.
The webpage is currently being hosted on Netlify and its build status is indicated in the above badge.