Descripción del proyecto
Algoritmos de inteligencia artificial para unos nuevos procedimientos de endoscopia poco invasivos
La cápsula endoscópica de colon es una nueva tecnología que podría sustituir a los actuales procedimientos de colonoscopia, que se asocian a molestias y complicaciones. Dicha tecnología presenta una baja tasa de complicaciones y no requiere ningún entorno hospitalario, pero conlleva la prolongada lectura de un manual y es proclive a los errores humanos. El objetivo del proyecto AICE, financiado con fondos europeos, es crear una vía respaldada por inteligencia artificial (IA) para el diagnóstico con cápsula endoscópica de colon, a fin de que esta sea clínicamente viable. El equipo de AICE utilizará diversos conjuntos de datos de pacientes ya existentes para completar y validar los algoritmos de IA para el diagnóstico con cápsula endoscópica de colon, crear un sistema de apoyo clínico para el tratamiento, el almacenamiento y la transmisión de datos, y promover la integración de la innovación de AICE en la práctica clínica.
Objetivo
Millions of Europeans undergo optical colonoscopy (OC) every year. OC may be associated with discomfort, complications and sick-days, which affect acceptability, and constitutes a heavy burden on European hospital capacities. Colon capsule endoscopy (CCE) is a new technology, which has the potential to replace 50 ? 65 % of all OCs. CCE is preferred by patients, has a lower complication rate and can be performed out of hospital. CCE holds great potential for both patients and hospitals. However, the diagnostic process of CCE includes a time-consuming manual reading done by trained personnel and is expensive and prone to human error. For CCE to be a viable alternative to OC these challenges need to be addressed. Thus, our goal is to create a complete and validated AI-assisted pathway that improves CCE diagnostics making the technology clinically viable for the good of patients, health care systems and society. We have already completed development of several AI algorithms (AIA) for CCE diagnostics, and more will be completed within 1 ?2 years. The AICE concept will focus on: 1) completing development of the remaining AIAs, 2) external validation the all AIAs, 3) creating a clinical support system for data handling, storage and transmission, 4) developing a diagnostic pathway that considers quality, efficiency, patient preferences, ethics and economy 5) promotes the integration of AICE solutions into clinical practice via guidelines and upscaling adjustments. To achieve these goals, AICE will use an unprecedented large and diverse collection of existing patient data from nation-wide clinical studies, and will include extensive initiatives in the fields of ethics, communication and patient engagement. To ensure the right competences are present, AICE brings together clinical researchers, epidemiologists, data scientists, digital health experts, health economists, ethics researchers, SMEs, communication experts and experts in regulatory affairs.
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinador
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