Software
Dream Team Software Engineering (DTSE) is our software development division. DTSE currently contains three subteams that are all focused on producing innovative technologies for the patients and doctors at Shands Hospital through a combination of web apps, mobile apps, VR games, and software-controlled hardware.
Diabetes VR
The Diabetes VR team collaborates with an endocrinology team at Shands to create an educational game in virtual reality for pediatric diabetes patients. The goal is to help patients learn about subjects like portioning, carb counting, and more in an engaging and immersive way which leverages the unique capabilities of virtual environments. We combine programming skills with art and game design using technologies including Unity with C# scripting and Blender.
Cardiology
The Cardiology team is focusing on a software application that is able to process and display a patient's heart scans in relation to an LVAD surgical implant so that the doctors in the Shands hospital has a visual aid to help them explain the surgical process to patients. The project's aim is to alleviate any stress on the patient side and inform them another way.
Train of Four
This team aims to automate the Train of Four test, which assesses anesthetic levels within a patient. The team combines computer vision with a TensorFlow/Keras image processing framework to accurately quantify hand movements of a patient after an electrical stimulus. This measurement tool standardizes and collects critical information that inform anesthesiologists on the effect and delivery of medications.
Air Embolism
We are collaborating with the CSSALT lab to create a project to detect venous air embolisms using a precordial doppler. Precordial dopplers can be placed over the heart to monitor the presence of air embolisms. Air embolisms occur when gas has entered the venous system, often during surgical procedures or clinical settings, and can result in patient fatality. Anesthesiologists currently monitor changes in sound in the doppler audio to detect air embolisms. This project involves automating and optimizing this process, allowing for real-time detection. The software will use doppler audio output, and the end project should be in the form of a standalone executable. The Air Embolism project is new for Fall 2023!
Disease Research and Infection Forecasting Tool (DRIFT)
The Disease Research and Infection Forecasting Tool (DRIFT) offers a predictive solution for Public Health organizations, medical facilities, and healthcare providers by forecasting disease incidence in specific localities. Leveraging a novel approach, the team combines spatial and temporal models to pinpoint disease hotspots and model disease transmission between regions of interest, generating precise forecasts of spread for the upcoming days and weeks.This capability enables healthcare professionals to better prepare for imminent disease outbreaks, significantly enhancing patient care in hospitals and bolstering public health efforts on a national scale.
CT GAN
The CT GAN team focuses on leveraging Generative Adversarial Networks (GAN) to create synthetic lung CT images to augment pulmonary disease datasets. A GAN is connective model that consists of a generator and discriminator; the generator creates synthetic data and the discriminator validates that data’s fidelity compared to the training dataset. This project aims to boost the quality of medical imaging diagnostic tools, especially around rare diseases, and can pave a better path to working with small datasets.
