Text mining and word embedding for classification of decision making variables in breast cancer surgery |
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| Affiliation: | 9. Department of Math and Computer Science, University of Catania, Catania, Italy;10. Department of Drug and Health Sciences, University of Catania, Catania, Italy;11. Breast Unit, University Hospital Federico II, Naples, Italy;12. University Hospital Heidelberg Departement of Gynecology - Breast Unit, Germany;13. Uppsala University Hospital, Breast Unit, Department of Surgery, Uppsala, Sweden;14. Breast Center University Hospital Basel, Switzerland;15. Department of Mastology and Professor of Surgical Oncology of the Institute of Oncology "Ángel H Roffo”. Buenos Aires University, Buenos Aires, Republica Argentina;p. Tufts Medical Center, Boston, USA;q. Hospital Nossa Senhora das Graças, Curitiba, Brazil;r. Department of Surgery, University of Helsinki and Helsinki University Hospital, Finland 2. Department of Surgery and Perioperative Sciences/surgery, Umeå University, Sweden;s. Federal University of Goias and Araujo Jorge Cancer Hospital, Gioania, Goias, Brazil;t. National and Kapodistrian University of Athens, Athens, Greece;u. Breast Surgical Oncology Unit Clinica Universidad de Navarra, Madrid, Spain;v. Aberdeen Royal Infirmary, NHS Grampian, Scotland, United Kingdom;w. Centro di Senologia della Svizzera Italiana, Ente Ospedaliero Cantonale, Lugano, Switzerland;x. Prashanti Cancer Care Mission, Pune, India;y. Liverpool University Hospitals Foundation Trust, Liverpool, UK;z. Addenbrooke''s Hospital, Cambridge, UK;11. Allegheny Health Network, Pittsburgh, USA;12. The Alfred Hospital, Melbourne, Australia;13. National Institute of Oncology, Budapest, Hungary;14. Breast Surgery, King Edward Medical University, Lahore, Pakistan;15. Department of Surgery, Marmara University School of Medicine, Istanbul, Turkey;16. University of Campinas, Campinas, Brazil;17. Breast Surgery Department of General Surgery, University of Wien, Austria;18. Department of Breast Surgery, Herlev Hospital, Herlev, Denmark;19. Breast Unit, Guy''s and St Thomas NHS Foundation Trust, London, UK;110. Breast Unit, Jiahui International Hospital, Shanghai, China;1. Multidisciplinary Breast Unit, Azienda Ospedaliera Cannizzaro, Catania, Italy;2. G.RE.T.A. Group for Reconstructive and Therapeutic Advancements, Milan, Naples, Catania, Italy;3. Department of Advanced Biomedical Sciences, University of Naples Federico II, Naples, Italy;4. Medpace, Bruxelles, Belgium;5. Department of Breast Surgery, Royal Marsden NHS Foundation Trust, Sutton, UK;6. Department for Surgical Sciences, Uppsala University, Uppsala, Sweden;7. Department of Pharmaceutical Sciences, University of Catania, Catania, Italy;8. Department of Drug and Health Sciences, University of Catania, Catania, Italy;1. Department of Surgical Sciences, Department of Colorectal Surgery, Uppsala University, 752 36, Uppsala, Sweden;2. Department of Surgical Sciences, Department of Colorectal Surgery, Uppsala University Hospital, S-751 85, Uppsala, Sweden;1. Department of Hepatobiliary and Pancreatic Surgery, Oxford University Hospitals NHS Foundation Trust, UK;2. Queen''s University Belfast, University Road, Belfast, Northern Ireland, UK;1. Peter MacCallum Cancer Centre, Division of Surgical Oncology, Australia;2. Sir Peter MacCallum Department of Oncology, University of Melbourne, Australia;3. Peter MacCallum Cancer Centre, Division of Medical Oncology, Australia;4. Peter MacCallum Cancer Centre, Division of Cancer Imaging, Australia;5. Peter MacCallum Cancer Centre, Division of Anatomical Pathology, Australia;1. Department of Surgical Oncology and Gastrointestinal Surgery, Erasmus MC Cancer Institute, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands;2. Department of Orthopaedic Oncology, Leiden University Medical Centre, Albinusdreef 2, 2333 ZA, Leiden, the Netherlands;3. Department of Radiotherapy, Erasmus MC Cancer Institute, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands;4. Department of Surgical Oncology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, the Netherlands;5. Department of Radiology & Nuclear Medicine, Erasmus Medical Centre, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands;1. Hepatobiliary Unit, Department of General and Digestive Surgery, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-IP), Universidad Autónoma de Madrid (UAM), Madrid, Spain;2. Division of Hepatobiliary and Liver Transplantation Surgery. A.O.R.N. Cardarelli, Napoli, Italy;3. Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore;4. Hepatopancreatobiliary Unit, Hospital del Mar, Barcelona, Spain;5. Hepatobiliary Unit, Fondazione Poliambulanza Istituto Ospedaliero Multispecialistico, Brescia, Italy;6. Hepatobiliary and Liver Transplant Unit, Hospital Universitario Cruces, Barakaldo, Bizkaia, Spain;7. Unit of General and Pancreatic Surgery, Department of Surgery and Oncology, University of Verona Hospital Trust, Italy;8. Yong Loo Lin School of Medicine, National University of Singapore, Singapore;9. HPB Surgery and Transplantation Unit, Department of Clinical and Experimental Medicine, Polytechnic University of Marche, Ancona, Italy |
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| Abstract: | IntroductionDecision making in surgical oncology of the breast has increased its complexity over the last twenty years.This Delphi survey investigates the opinion of an expert panel about the decision making process in surgical procedures on the breast for oncological purposes.MethodsTwenty-seven experts were invited to partake into a Delphi Survey. At the first round they have been asked to provide a list of features involved in the decision making process (patient's characteristics; disease characteristics; surgical techniques, outcomes) and comment on it. Using text-mining techniques we extracted a list of mono-bi-trigrams potentially representative of decision drivers. A technique of “natural language processing” called Word2vec was used to validate changes to texts using synonyms and plesionyms. Word2Vec was also used to test the semantic relevance of n-grams within a corpus of knowledge made up of books edited by panel members. The final list of variables extracted was submitted to the judgement of the panel for final validation at the second round of the Delphi using closed ended questions.Results52 features out of 59 have been approved by the panel. The overall consensus was 87.1%ConclusionsText mining and natural language processing allowed the extraction of a number of decision drivers and outcomes as part of the decision making process in surgical oncology on the breast. This result was obtained transforming narrative texts into structured data. The high level of consensus among experts provided validation to this process. |
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| Keywords: | Breast surgery |
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