Completed Intern Projects


Wave 6 - January to June 2024


Wave 5 - June to November 2023


Wave 4 - January to May 2023

  • P43 - Enriching Neurology Patient Information using MedCAT

    In collaboration with Lancaster Teaching Hospitals NHS Foundation Trust and Lancaster University, this work explored how to evaluate the embedding space generated for automated clinical coding tasks in Neurology.

    Published Report

    NLP Neurology Python - MedCAT
  • P42 - Including Mortality in Hypergraphs for Multi-morbidity

    Building on previous hypergraphs work (P34) that can extract the impact of predecessor and successor diseases on disease progression pathways, this work looked to include an implicit relationship to demographics and consider the impact of mortality.

    Published Report

    Representations of Data Hypergraphs Python - Numba
  • P41 - NHS Synth

    This project focused on building a package for generating useful synthetic data, audited and assessed along the dimensions of utility, privacy and fairness. It gives the ability to experiment with different model architectures to find which are the most promising for real-world usage.

    Published Report

    Synthetic Data VAE Python

Wave 3 - June to December 2022


Wave 2 - January to May 2022

  • P24 - Using LIME to explain facial disease classification

    Application of Local Interoperable Model-agnostic Explanations to an InceptionV3 classifier looking at a Rosacea

    Published Report

    Model Explainability LIME Python
  • P23 - STM for survey data

    The development of an R code for investigating the topics found in free text survey data using a technique that monitors both the content of the responses but also the metadata.

    Published Report

    RAP code Topic Modelling R
  • P22 - Txt-Ray Align

    An investigation of extracting insight from multi-modal text and imaging data using contrastive learning.

    Published Report

    Multi-modal Contrastive Learning Python
  • P21 - SynthVAE Continued

    Building on SynthVAE - focused on non-Gaussian input data, hyperparameter tuning, improving the codebase and starting to consider how fairness in the created data can be assessed and implemented.

    Published Report

    Synthetic Data VAE Python - PyTorch, Opacus

Wave 1 - April to September 2021

  • P14 - Model Class Reliance

    Investigating the use of MCR to identify the value of including commercial sales data in respiratory predictions

    Published Report

    Model Explainability Commercial Data Python - mcrforest, SHAP
  • P13 - NHS Text Data Exploration

    Using a pre-defined toolset this project looked to understand how to ingest NHS.UK text data into a curated form.

    Published Report

    NLP Weak Supervison Python - scispaCy
  • P12 - SynthVAE

    Initial creation of a variational autoencoder with differential privacy for generating single table tabular gaussian data.

    Published Report

    Synthetic Data VAE Python - PyTorch, Opacus
  • P11 - SynPathDiabetes

    Exploration work into incorporating learning in to a pathway simulator for diabetes.

    Published Report

    Simulation Patient Pathways Python