In 2021, our team started development of a LoRaWAN network (see link) to cover the University of Kentucky campus/hospital and most, if not all, of Lexington (see link). This project is still active as we continue to develop new applications, but creating infrastructure to support this network has become a…
Abnormality Detection in Mammograms Using Segment Anything
In early April 2023, Meta AI released Segment Anything (SAM), an machine-learning based segmentation model. The repository model of SAM operates on a very general image database, so we have been re-training SAM to specifically process mammograms and identify any abnormalities within. In 2020, it is estimated that there were…
Real-Time Visualization Interface for Smell Sensor
We developed a program that visualizes the raw input data and ML-based smell detection analysis of the SmartNanotubes Smell Inspector. The Smell Inspector is based on electronic nose (E-nose) technology that uses nanomaterial elements to detect odors or volatile organic compounds (VOCs). Classification of smells occurs through pattern recognition algorithms…
CLASSify- A Web-based Tool for Machine Learning
Clinicians often produce large amounts of data, from patient metrics to drug component analysis. Classical statistical analysis can provide a peek into data interactions, but in many cases, machine learning can provide additional insight into new features. Recently, with the boom of new artificial intelligence models, these clinicians are more…
Survey of Machine Learning Techniques To Predict Heartbeat Arrhythmias
Abstract - Many works in biomedical computer science research use machine learning techniques to give accurate results. However, these techniques may not be feasible for real-time analysis of data pulled from live hospital feeds. In this project, different machine learning techniques are compared from various sources to find one that…
UK Digital Twin Environment to Transport Clinical Specimens using AI
Introduction: The Institute for Biomedical Informatics is always looking for ways to improve the efficiency of our hospital system. One way to do this is through the transportation of clinical specimens from Chandler Hospital to Shriner's Hospital and Good Samaritan Hospital using AI pathfinding and collision avoidance. By training a…
Using NVIDIA Speech AI and Rasa to Create a Multi-Use Chatbot
Introduction: An issue for our healthcare facilities as well as many others around the country is better understanding the needs of patients. If a patient has experienced a form of trauma, talking to a doctor face-to-face may be difficult. This is where the NVIDIA Omniverse can help doctors extract vital…
Distributing Workloads over Esports Gaming Computers to Train Machine Learning Models
As machine learning models become more and more computationally complex, there is a need for high-performance computing architecture. With the newly opened Esports lounge, there is an opportunity to utilize 30+ machines using the top-spec hardware. Cresco in conjunction with ClearML is being used to train cancer predicting models for…
Creation of a Distributed LoRaWAN Network to Cover the UK Campus
Abstract - Long Range Wide Area Network (LoRaWAN) is an emerging technology that uses low-cost, low-energy intermediate gateways between a central network and end devices. Starting in 2009, LoRaWAN has gained popularity and has been deployed in many environments including agriculture, healthcare, and cities. With the tremendous amount of data…
Hepatitis A Predictor
Link to Hepatitis A Predictor