RALPulator : Predicting Robotic-assisted laparoscopic prostatectomy (RALP) operative times from patient letters

30 Second Summary

This project is an app that reads in patient letters ahead of surgery, using Natural Language Processing techniques to extract key information from the text, and then feeds all of that into a Machine Learning model which then predicts how long the Robotic-assisted laparoscopic prostatectomy (RALP) surgery is going to take.

Machine Learning

Natural Language Processing (NLP)

Streamlit

Urology

Cancer

Surgical

NHS 10-year big bet: AI to drive productivity

NHS 10-year plan shifts: Sickness to Prevention

This project is building an app that reads in patient letters ahead of surgery, uses Natural Language Processing techniques to extract key information from the text, and then feeds all of that into a Machine Learning model which then predicts how long the Robotic-assisted laparoscopic prostatectomy (RALP) surgery is going to take.

A first version of the app has been developed and deployed, and is available here: https://ralpulator.streamlit.app/

Jake is presenting the work to the National Urological Conference in November 2024, and has been invited to present in Perth, Australia in March 2025.

10-year plan Alignment

“NHS 10-year big bet: AI to drive productivity”: using NLP and machine learning to extract information from patient letters and predict robotic-assisted surgery duration, supporting more efficient theatre scheduling.

“NHS 10-year big bet: robotics to support precision”: supporting the planning and resourcing of robotic-assisted laparoscopic prostatectomy surgery, a technology already transforming precision in surgical care.