OUR HISTORY
THE BEGINNING
The AIDPRO manual CRC is a clinical decision support tool designed for colorectal surgeons managing perioperative care for patients undergoing elective curative surgery for colorectal cancer. It uses a prediction model trained on national Danish data to estimate a patient’s one-year mortality risk and categorizes them into risk strata to guide perioperative treatment planning. While the tool provides recommendations, surgeons retain full decision-making authority and can override suggestions when necessary.
The algorithm was developed using extensive patient data from national health registries, with a structured selection process ensuring relevant clinical variables are included. Performance validation was conducted to ensure accuracy and reliability. The tool is accessed through a secure platform, requiring manual data input by authorized colorectal surgeons.
A dedicated graphical user interface (GUI) called MDTplus has been designed to integrate with the AIDPRO manual CRC. MDTplus serves as the user interface, providing a secure and structured environment for surgeons to input patient data and receive risk estimations. The system operates as a web, ensuring seamless accessibility during multidisciplinary team meetings and preoperative consultations. The platform is designed to support, rather than replace, clinical judgment in colorectal cancer surgery planning.
2018: EPeOnc
In January 2018, Ismail created the Enhanced Perioperative Oncology (EPeOnc) consortium at ZUH with the aim to combine principles of optimized surgical, anesthesiological and oncological treatments to improve short- and long-term outcome of patients undergoing cancer surgery.
2019: CAG-POS
In June 2019, his work within data science and personalized medicine was internationally acknowledged be appointing him the chairperson of a clinical academic group within personalized oncological surgery (CAG-POS). The CAG-POS provided the framework for efficient use of Big Data and artificial intelligence (AI) in Personalized Medicine (PM) to develop high-risk prediction models using Danish register data and to validate and implement the models in the clinical setting. On February 1, 2023, the prediction model was implemented as an evidence-based decision-support tool to stratify patients with CRC into four risk profiles based on their predicted 1-year mortality
2021: THE ESTABLISHMENT OF OUR LABORATORY
In January 2021, Ismail established a state-of-the-art research laboratory at ZUH. The vision for the laboratory is to perform pre-analytical and analytical analyses on tissue and blood samples collected in the perioperative period from patients enrolled in clinical phase I/II intervention or medical studies. The goal is to integrate translational data into the prediction model.