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Hello 👋

I’m Thomas Padgett, a principal health data scientist at HEOR, ex-aerospace engineer, with a PhD in computational fluid dynamics and agent-based modelling. I'm big on nature, being outside, plants, and mountains. 🌱🌱🌱

On-going work ✨

» Machine learning and data analytics using real world data (CPRD/HES).
» Derivation of risk equations from clinical trials.
» Population-level infectious disease modelling & vaccine public health impact.
» Early drug pricing/revenue forecasting, inc. optimisation approaches for market access launch sequencing.

Interests 👀

» Heuristic optimisation techniques and their application to health.
» Health economic evaluations in R, particularly simulation (individual-level) models for obesity and diabetes.
» Building simple example models on Github (PSM, cSTM, SEIR, etc.)

Thomas Padgett's Projects

age_structure_predictor icon age_structure_predictor

This project considers the prediction of the age structure/population pyramid of the United Kingdom based on ONS/UN data for birth rates, mortalities, and net migration values starting with initial an age structure based on ONS data for 1991. Birth rate and net migration data are predicted up to 2100 by the UN. Mortality rates per age group are predicted up to 2100 using the mortalityPredictor.py script.

desire_paths icon desire_paths

This script simulates desire paths in a 2D domain using a biased A* algorithm, and pre-defined path and obstacle locations.

genetic_algorithm_tsp icon genetic_algorithm_tsp

A bespoke python genetic algorithm to solve the generalised 2D travelling salesman problem.

padj icon padj

Config files for my GitHub profile.

r_ibm_example icon r_ibm_example

Example workings for individual-based modelling approaches in R

r_psm_example icon r_psm_example

*Incomplete* Example partitioned survival model (PSM) in R for Nivolumab versus Ipilimumab in melanoma (with some stuff made up).

r_seir_zombies icon r_seir_zombies

Example SEIR modelling approaches using zombie apocalypse as an example.

strokepredictionml icon strokepredictionml

Documenting ML approaches to predicting which patients suffer stroke, based on the Kaggle strokePrediction dataset available at: https://www.kaggle.com/fedesoriano/stroke-prediction-dataset

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