TRAIN-AI is a research project whose purpose is the prognostic analysis in the medical field with reference to the tumor pathology known as HCC (hepatocarcinoma). This tool based on deep learning allows you to perform a regression of the probability of tumor recurrence following liver transplantation. In particular the starting architecture used is the Deep Surv neural network. Enter patient data to perform the recurrence prediction shown through a responsive graph.
Remember that TRAIN-AI is a non-linear regressor: varying a single feature does not imply an intuitive behavior of the result.
TRAIN-AI is the result of a large international effort involving several liver transplant centers coming from Western and Eastern World. The collaborating centers composed two international study groups, namely the EURopean HEpatocellular CAncer Liver Transplantation (EURHECALT) Study Group and the West-East Liver Transplant Study Group.
Asia Queen Mary Hospital, University of Hong Kong, Hong Kong SAR of China; Medanta-The Medicity, Gurgaon, India; Kyushu University, Fukuoka, Japan; Graduate School of Medicine, Kyoto, Japan; Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Europe Medical University of Innsbruck, Innsbruck, Austria; Université catholique de Louvain, Brussels, Belgium; Merkur University of Zagreb, Zagreb, Croatia; Universitätsmedizin Mainz, Mainz, Germany; Polytechnic University of Marche, Ancona, Italy; Bologna University, Bologna, Italy; University of Padua, Padua, Italy; Catholic University - Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy; San Camillo Hospital, Rome, Italy; Sapienza University of Rome, Italy; University of Rome-Tor Vergata, Rome, Italy; Royal Free Hospital, London, UK.
United States Columbia University, New York.
Professor emeritus of Surgery and scientific collaborator of the Institute for Clinical and Experimental Research (IREC) of the Université Catholique Louvain (UCL). During both his surgical training and career, he got acquainted with five different linguistic and cultural European environments (Dutch, German, English, French, Polish speaking). This situation together with his longstanding interest for and exposure to Asian medicine and surgery, allowed him to get a unique insight in the today’s surgical world. A worldwide network, build-up during the recent decade, resulted in the creation of both the EURHECALT and the West-East LT Study Groups.
Assistant Professor at Sapienza University of Rome. He is the data-manager of both the EURHECALT and the West-East LT Study Groups. Dr Lai is expert in clinical studies, specializing in clinical data management, statistic evaluations, data communication, and publication.
Computer engineer and currently student of Data Science and Engineering at the Polytechnic University of Turin. Creator of the TRAIN-AI deep model and developer of the web application proposed in this page. For technical problems about the tool contact me!
Authors and Contributors
Quirino Lai 1 • Carmine De Stefano 2 • Jean Emond 3 • Prashant Bhangui 4 • Toru Ikegami 5 • Benedikt Schaefer 6 • Maria Hoppe-Lotichius 7 • Anna Mrzljak 8 • Takashi Ito 9 • Marco Vivarelli 10 • Giuseppe Tisone 11 • Salvatore Agnes 12 • Giuseppe M. Ettorre 13 • Massimo Rossi 1 • Emmanuel Tsochatzis 14 • Chung Mau Lo 15 • Chao-Long Chen 16 • Umberto Cillo 17 • Matteo Ravaioli 18 • Jan P Lerut 19 on behalf of the EurHeCaLT and the West-East LT Study Group.
1. General Surgery and Organ Transplantation Unit, AOU Policlinico Umberto I, Sapienza University of Rome, Italy; 2. Data Science and Engineering, Polytechnic of Turin, Italy; 3. Division of Liver Transplantation and Hepatobiliary Surgery, Department of Surgery, Weill Cornell Medicine - Columbia University, New York, US; 4. Medanta Institute of Liver Transplantation and Regenerative Medicine, Medanta-The Medicity, Gurgaon, India; 5. Department of Surgery and Science, Kyushu University, Fukuoka, Japan; 6. Medical University of Innsbruck, Department of Medicine I, Gastroenterology, Hepatology and Endocrinology, Innsbruck, Austria; 7. Klinik für Allgemein-, Viszeral- und Transplantationschirurgie, Universitätsmedizin Mainz, Mainz, Germany; 8. Liver Transplant Centre, Merkur University of Zagreb, Zagreb, Croatia; 9. Division of Hepato-Biliary-Pancreatic and Transplant Surgery, Department of Surgery, Graduate School of Medicine, Kyoto, Japan; 10. Unit of Hepatobiliary Surgery and Transplantation, AOU Ospedali Riuniti, Polytechnic University of Marche, Ancona, Italy; 11. Department of Surgical Sciences and Medical Sciences University of Rome-Tor Vergata, Rome, Italy; 12. Liver Unit, Department of Surgery, Catholic University - Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy; 13. Department of Transplantation and General Surgery, San Camillo Hospital, Rome, Italy; 14. UCL Institute for Liver and Digestive Health and Royal Free Sheila Sherlock Liver Centre, Royal Free Hospital, London, UK; 15. Hong Kong University – Department of Surgery, Queen Mary Hospital, University of Hong Kong, Hong Kong SAR of China; 16. Department of Surgery, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan; 17. Department of Surgery, Oncology and Gastroenterology, University of Padua, Padua, Italy; 18. Department of General Surgery and Transplantation, IRCCS, Azienda Ospedaliero-Universitaria di Bologna, Bologna University, Bologna, Italy; 19. Institut de Recherche Clinique, Université catholique de Louvain, Brussels, Belgium.