Embedded Artificial Intelligence (EAI)-based prognostics

 

  

Prof. Francesco Corcione, Prof. Pasquale Arpaia, Prof. Roberto Prevete.

Goals

  • Reduce the clinical risk in surgical procedures by implementing an embedded artificial intelligence (EAI);
  • Helping the surgeon in prognostics assessing the quality of the outcome of the procedure;
  • As a case study, the AI-based automatic evaluation of the quality of the suture of the gastrointestinal tract, based on the vascularization analysis applied to abdominal laparoscopic surgery.

Results

  • The system has been already tested during a surgical procedure: results showed that the developed algorithm successfully identifies, in real time,  well- and low-vascularized tracts; 
  • Further research is dedicated to implementing different thresholds levels to quantify the success of the procedure.

Keywords

Artificial intelligence, surgery, indocyanine green-based fluorescence, laparoscopic surgery, decision support system.

Projects

«Chirurgia Aumentata. Mixed reality a supporto dell’attività chirurgica» (Bando POR CAMPANIA FESR 2014/2020 Asse Prioritario 1 "Ricerca e Innovazione").

Print