My name is Gary Hutson and I have been working in the public sector for over 17 years, splitting my time between Nottinghamshire Police, Nottinghamshire County Council and Nottingham University Hospitals. I have worked for a private sector healthcare company specialising in AI and predictive integration into dashboards, in these roles I was a Senior Data Scientist and Head of Data Science and AI. Recently, I have joined Arden & GEM commissioning support unit as the Head of Advanced Analytics.
I have expertise and interest in the following areas:
- Object Orientated Programming i.e. C#
- VBA for Excel and Access
- Machine Learning
- Deep Learning
- Packages such as H2O.ai, Keras, MxNet, CARET, SciKit-Learn, OpenCV and Tensorflow (accredited Tensorflow Developer)
I enjoy anything technical and have worked on a number of interesting projects in my time, deploying the right analytical technique for the job.
In the past eight years I have gotten involved in Machine Learning in a big way and have deployed algorithms to use NHS information better. Notable successes are the ED prediction project, forecasting (time series) of patients on a 62 day cancer pathway, segmentation using clustering of the acuity of patient cohorts, spatial analysis of crime hot spots and using Kernel Density Estimation to produce heat maps and predictions. As well as lots and lots of regression.
In 2019, I joined Draper & Dash as the Head of Data Science and AI, a predictive healthcare analytics firm. Notable successes hitherto have been:
- Leading on our AI / ML training course e.g. introduction to data science, ML training days (2 day courses focused on supervised and unsupervised learning) and working closely as an Associate to the NHS-R Community
- Pathway clustering and associative rule mining of mental health pathways
- Supervised learning models, augmenting the dashboard and BI offerings in the company, the biggest sellers are our readmission avoidance, stranded / long stayer predictors, LOS estimator, radiology turnaround times and OP cancellation predictors.
- Unsupervised machine learning – clustering secondary care patients based on acuity and disease prevalence using R and Python libraries – integrated with reticulate
- Custom forecasting tools deployed into our Command Centre offering (https://draperanddash.com/machinelearning/command-centre-amplification-with-predictive-analytics-and-machine-learning/).
- Researching how our Computer Vision skill sets can be used for Image / Video classification, relating to detection of irregular scans
I have a strong passion for upskilling our NHS workforce with the data science and mathematical skills needed to develop effective solutions. We regularly hold various training events and I look forward to seeing you at one in the future: