Machine learning to identify, track, and monitor disease

Principal Investigator
Name: John MacLean
Degrees: BMBS, BSc
Institution: doclink.io
Position Title: Chief Medical Officer
Email: maclean.john@gmail.com

Project Information
Study: NLST
Project ID: NLST-338
Title: Machine learning to identify, track, and monitor disease

Summary
We are attempting to develop a machine learning-based platform to aid clinicians in the diagnosis of lung lesions, using radiological and histological images from the NLST as a means to train our system. A minority of the data will be used to validate our system to help ensure it can meet the clinical standards required.

Aims
1. Develop a system that can aid in an initial radiological diagnosis of patients that have the clinical signs of symptoms of lung pathology.
2. Develop a system that can subsequently aid the clinicians in the followup of patients with confirmed lung pathology.
3. Develop a system that can correlate the radiological images with the histopathological images of the lung resection specimens.
4. Use a portion of the data as a means of validating our system

Collaborators

No one outside of doclink.io