{"id":25869,"date":"2021-12-13T08:40:25","date_gmt":"2021-12-13T07:40:25","guid":{"rendered":"https:\/\/www.ita.es\/proyecto\/ai4eu-colonlp\/"},"modified":"2023-12-04T13:59:44","modified_gmt":"2023-12-04T12:59:44","slug":"ai4eu-colonlp","status":"publish","type":"proyecto","link":"https:\/\/www.ita.es\/en\/project\/ai4eu-colonlp\/","title":{"rendered":"AI4EU – COLONLP"},"content":{"rendered":"\r\n
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PROJECT TITLE:<\/h2>\n\n\n\n

Transformers & Graph Algorithms against colon cancer (AI4EU – ColoNLP)<\/p>\n\n\n\n

GENERAL DATA:<\/h2>\n\n\n\n

Program: AI4EU OPEN CALL FOR SOLUTION – H2020Ref. No.: 82519RESOLUTION Date: 02\/08\/2021Execution date: 29\/06\/2021-16\/12\/2021<\/p>\n\n\n\n

PRESENTATION AND OBJECTIVES:<\/h2>\n\n\n\n

The main objective of the project is to develop a tool that, given a free medical text, using natural language processing (NLP) techniques, is capable of automatically extracting and identifying ICD-10 diagnosis and procedure codes.The ultimate goal is to help, with the extraction of ICD-10 codes and in combination with molecular characteristics, to improve the algorithm available to Amadix for the prediction of colorectal cancer and to identify the population at high risk for colorectal cancer.The main contribution of ITAINNOVA to the challenge presented by AMADIX is the implementation of an intelligent system, using Artificial Intelligence techniques and especially deep analysis techniques for the prevention of colon cancer based on the analysis and recognition of patterns in texts of patients’ medical records. The main idea is, using natural language processing (NLP) techniques focused on the Spanish language, to identify on these documents what other pathologies the patients suffer from and map them into the ICD-10 codes, which are standard codes for diseases and procedures, and to identify different comorbidities that could affect the development of colorectal cancer. Once the clinical records have been analyzed to obtain the data, these data will be combined with the results of the blood tests developed by AMADIX, to create Artificial Intelligence based models that allow:<\/p>\n\n\n\n

– Generate action plans aimed at the target population to prevent colorectal cancer or detect it at an early stage.– To identify potential profiles of people at high risk of developing cancer in its early stages and thereby reduce treatment costs and reduce the risk of death.– Centralize information to generate statistics and detect problems more quickly.<\/p>\n\n\n\n

PARTICIPATING ENTITIES:<\/h2>\n\n\n\n

Instituto Tecnol\u00f3gico de Arag\u00f3n ITAINNOVA (individual call)<\/p>\n\n\n\n

BUDGET:<\/h2>\n\n\n\n

TOTAL BUDGET ITAINNOVA: 70.000 \u20ac.<\/p>\n\n\n\n

FINANCING:<\/h2>\n\n\n\n

TOTAL FINANCING ITANNOVA: 70.000 \u20ac.This project has received funding from the European Union’s Horizon 2020 research and innovation programme within the framework of the AI4EU Project funded under grant agreement n\u00ba 825619.<\/p>\n\n\n\n

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