Data analysis and presentation for tick and tick-borne disease surveillance

The main objective of this project is to analyze and display data collected passively through our tick testing service. Part of our mandate as a company is to to publish tick and tick-borne disease surveillance data yearly based on data collected from ticks submitted to our laboratory for testing. This data includes spatial and temporal information about where and when ticks were encountered, what activities users were engaged in when they encountered the ticks, the types of pathogens detected in each tick, and which demographics are disproportionately affected. In previous years, this data has been analyzed and displayed using accessible tools such as Microsoft Office Suite (Excel, Powerpoint) and Google MyMaps. This year, we are looking to improve the data analysis and presentation by using more powerful statistical and GIS tools. Previous examples of this work can be seen on our website at https://www.geneticks.ca/tick-testing-statistics/.

RAIN - Artificial Intelligence & Machine Learning Application

Our company offers a machine learning application, and we want to leverage the latest technology to gain market advantage. Applications of this technology include clinical support algorithms, predictive analytics for waitlist, and automatic reporting. We would like to collaborate with students to apply the latest artificial intelligence (AI) and machine learning (ML) techniques and have a market analysis done with a marketing strategy. This will involve several different steps for the students, including: Conducting background research on our existing products and the dataset. Analyzing our current dataset. Researching the latest AI / ML techniques and how they could be applied to our data. Developing predictive analytics that customers across the industry are interested in. Providing multiple solutions that can be applied to solve the same problem.