An intelligent system to improve patients’ safety and remote surveillance in follow-up for cardiothoracic surgery



The COVID-19 pandemic caused several surgeries to be delayed or performed under emergency circumstances due to activated hospital protocols to reduce nosocomial transmission of this severe air-transmitted virus. Cardiac surgery is a vital medical intervention for the treatment of cardiac disease, being highly susceptible to severe postoperative complications, and which recovery follow-up is crucial in the post-op period. Due to cardiac patients’ frail health, these patients are identified as a risk group in pandemic contexts, being inadvisable hospitals visits due to high risk of infection.

CardioFollow.AI joints the multi-domain expertise of researchers from VOH.CoLAB, FhP-AICOS, NMS-UNL and HSM-CHULC. It tackles current limitations by introducing a telemonitoring service in Cardiothoracic Surgery Service of HSM-CHULC, to support clinicians in the follow-up of cardiothoracic surgery patients after hospital discharge. An Internet-of-Things (IoT) system will remotely collect daily outcomes of monitored patients to complement and improve the current follow-up process, which consists of periodic phone calls and consultations over the first year after the procedure.

An Artificial Intelligence (AI) module will leverage electronic health records (EHR) and patient follow-up data collected by clinicians since 2011. Patients will take home a telemonitoring kit that will automatically record a set of clinical parameters (ex. weight, blood pressure, heart rate). Through an intelligent natural conversation module, patients will self-report symptoms and receive automatic feedback from processed clinical notes. The multimodal data collected from patients’ health pathways will identify risks of complications throughout the follow-up process, namely: (1) estimate, in the pre-surgery period, optimal follow-up resources; (2) identify patients who will benefit the most from telemonitoring; and (3) early detection of complications at home which leads to prompt medical intervention. We plan on conducting a value-based study with the involvement of 154 patients.

CardioFollow.AI integrates into a single platform inpatient and outpatient monitoring data collected from clinicians, a telemonitoring system for the continuous registry of outcomes, and AI-based modules to longitudinally predict risk and early detect complications. The benefits of telemonitoring may extend from the pandemic context to regular times, where the optimization of the cost-benefit of eHealth procedures is of extreme importance in National Health Systems. With CardioFollow.AI, we plan on elevating CHULC-HSM follow-up service as the gold standard for other national and worldwide cardiothoracic surgery departments and contribute with a value-based approach to lower nosocomial transmission of COVID-19 and future pandemics, while ensuring proper care for citizens in need.


Project Duration:
36 months (January 2021 to December 2023)


Funded by:

"CardioFollow.AI - An intelligent system to improve patients’ safety and remote surveillance in follow-up for cardiothoracic surgery” project, with reference DSAIPA/AI/0094/2020, is a joint project with Fraunhofer AICOS, VOH.COLAB, NMS-UNL and HSM-UNL, financially supported by national funds through ‘FCT – Foundation for Science and Technology’ in the scope of “AI 4 COVID-19: Data Science and Artificial Intelligence in the Public Administration to strengthen the fight against COVID-19 and future pandemics – 2020."


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