Ongoing and upcoming research projects

Project 1: Pre-Operative Optimization of Patients with IBD
This project investigates different aspects of pre-operative optimization of patients with inflammatory bowel disease.
The first study in this project was also the first #OpenSourceResearch collaboration.
The project is based on a litterature review (published), cohort study (published) and computer simulation model of a randomised controlled trial.

Project 2: Patient-Reported Outcome in Colorectal Surgery
This project is based on three steps:

1. Litterature review
2. Construction of search algorithm
3. Validate the algorithm.

Project 3: De-Identification of Health Care Data
The project was launched in November 2020. It started with a literature review about algorithms and software used in data anonymization/de-identification.
It will be followed up by two other related studies.

Project 4: Collaboration in Research
The project is based on many studies that investigate collaboration in surgical research.

Project 5: Using AI to Extract Data from Medical Records
This project is based on three steps:

1. Litterature review
2. Construction of search algorithm
3. Validate the algorithm.

Project 6: Using AI to Extract Patterns from Blood Investigations
This is a project to be conducted with help from researchers in bioinformatics and datalogy.

Project 7: Using AI to Improve early Discharge of Hospitalized Patients
By crunching big data which includes daily vital signs charts, blood and microbiological investigations, we can study patterns of recovery. This may help in making decision about early discharge from the hospital.

Project 8: Improving outcome measurements of pre-operative optimization bundles
Pre-operative optimization is gaining momentum and more focus but how to measure the otcome of pre-operative optimization bundles? 

Project 9: Patterns of contact with primary and secondary health care systems to predict disease activity in patients with IBD
Pattern recognition is widely used in software solutions. It can also solve some clinical questions.

Project 10: Deciphering the Chronic Abdominal Pain with no Detectable Pathology Using Pattern Recognition Algorithms (Big Data Mining)
About 10% of patients have unexplained chronic abdominal pain. Most of them develop symptoms of diseases with time. This project investigates a large cohort of patients using their medical records.

Project 11: Predicting anastomotic leak using pre-operative abdominal scan
Computerized tomography scan can provide crucial information about arterial supply og the gut. Can this predict anastomotic leak?

Project 12: Predicting local-regional recurrence patterns
To study patterns of local-regional recurrence in colon cancer. First study used Danish Colorectal Cancer Group dataset. Second study is a systematic review. Then third will be to use AI to crunch data from scans.