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…
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…
Web-Based Segment Anything for Segmenting Medical Images
Segment Anything is a segmentation algorithm created by Meta Research. In order to try and make segmentation of medical images available to UK Hospital staff, a web interface which allows for the layperson to interact with segmentation should be utilized. Meta Research provided a sample web interface which precompiled…
Distributed Pharmaceutical Supply Management Using Hyperledger Fabric
Blockchain technology is a still emerging field that is seeing increased usage beyond its conception in decentralized banking. One field where that poses a unique challenge for blockchain adoption is healthcare, where data security of Protected Health Information (PHI) is of utmost importance. [caption id="" align="aligncenter" width="2031"] https://www.slalom.com/insights/how-blockchain-will-disrupt-your-industry[/caption] This project,…
Time Series Forecasting
Time series forecasting is the process of analyzing historical data in order to draw conclusions and predict future outcomes. For this project, we explore, compare, and contrast different methods and models of forecasting to determine the advantages and disadvantages of these different systems. We explore, through research papers and code…
Library support for Philips iSyntax format
The Philips iSyntax format is not directly supported by common open source digital pathology libraries. Currently, in order to use iSyntax files outside of the Philips environment one must either use the iSyntax SDK or convert iSyntax files to a supported format such as TIFF. The iSyntax SDK Terms &…
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…
Blockchain Applications for Healthcare Communications
Abstract- As a relatively new technology, Blockchain’s applications are still being explored in many fields. Its usage for the secure storage of data makes it an ideal candidate to update the modern healthcare communication system. Currently, hospitals in the United States have no good way to securely communicate important patient…