{"id":25655,"date":"2025-10-24T13:38:17","date_gmt":"2025-10-24T11:38:17","guid":{"rendered":"https:\/\/www.nefrocenter.it\/?post_type=progetto_di_ricerca&#038;p=25655"},"modified":"2025-11-29T15:53:57","modified_gmt":"2025-11-29T14:53:57","slug":"siate","status":"publish","type":"progetto_di_ricerca","link":"https:\/\/www.nefrocenter.it\/en\/progetto_di_ricerca\/siate\/","title":{"rendered":"SIATE"},"content":{"rendered":"\n<p>The SIATE project uses Artificial Intelligence (AI) to&nbsp;<strong>monitor and personalize hemodialysis therapy in real &nbsp; time:&nbsp;<\/strong>developing a digital platform that captures clinical data, analyzes it with AI, and helps clinicians tailor &nbsp; therapy to each patient, integrating smart monitoring, mobile and telemedicine tools, and decision support &nbsp; systems to enable personalized, preventive kidney care.<\/p>\n\n\n\n<p>Patients with chronic kidney disease undergoing dialysis often face serious health risks due to&nbsp;<strong>metabolic &nbsp; imbalances and inefficient treatment<\/strong><\/p>\n\n\n\n<p>Move from reactive treatment to&nbsp;<strong>predictive, AI-guided care&nbsp;<\/strong>that reduces complications, improves vascular &nbsp; access management, and&nbsp;<strong>enhances quality of life<\/strong><\/p>\n\n\n\n<p><strong>AIM<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>To develop\u00a0<\/strong>an AI-powered system that enhances the quality, precision, and accessibility of hemodialysis therapy by:\n<ul class=\"wp-block-list\">\n<li>Automatically monitoring vascular access (VA) performance through early alert generation, enabling preventive rather than \u00a0 corrective interventions<\/li>\n\n\n\n<li>Supporting clinical decisions by assessing metabolic and nutritional control on a per-patient basis<\/li>\n\n\n\n<li>Estimating dialysis efficiency via innovative sensors capable of simultaneously measuring standard and novel biomarkers in blood, dialysate, and exhaled air<\/li>\n\n\n\n<li>Standardizing therapies and objectively recording metabolic events for consistent clinical intervention<\/li>\n\n\n\n<li>Expanding the use of home dialysis through telemonitoring and AI-guided therapy adjustments<\/li>\n\n\n\n<li>Creating large-scale, structured databases for Network Medicine and AI applications in both clinical and market-oriented research<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p><strong>Method<\/strong><\/p>\n\n\n\n<p><strong>Nine implementation phases (Objectives \u2013 OR):<\/strong><\/p>\n\n\n\n<p><strong>1)<\/strong>&nbsp;Upgrade and automation of the existing VA triage system, initially manual, to serve 1,500 &nbsp; hemodialysis patients with real-time data acquisition and adaptive learning capabilities<\/p>\n\n\n\n<p><strong>2)<\/strong>&nbsp;Design of a clinical data acquisition and storage system to feed AI algorithms for decision-making model training<\/p>\n\n\n\n<p><strong>3)<\/strong>&nbsp;Development of a Clinical Decision Support System (CDSS) that integrates AI-driven decision rules into clinical workflows<\/p>\n\n\n\n<p><strong>4)<\/strong>&nbsp;Creation of a predictive system, based on clinical data, for personalized risk assessment and therapeutic planning<\/p>\n\n\n\n<p><strong>5)&nbsp;<\/strong>Implementation of a smart infrastructure to collect data from dialysis monitors and common devices (e.g., bioimpedance analyzers, blood gas machines, scales), enabling AI-based forecasting of clinical events<\/p>\n\n\n\n<p><strong>6)&nbsp;<\/strong>Deployment of a cloud-based infrastructure for storing and processing clinical data, supporting CDSS operations and AI model evolution<\/p>\n\n\n\n<p><strong>7)&nbsp;<\/strong>Design and release of a Data Portal for Medical Devices &amp; Patient Data, making clinical and monitoring data available to AI processing modules<\/p>\n\n\n\n<p><strong>8)&nbsp;<\/strong>Analytical method development for measuring both known (targeted) and novel (untargeted) biomarkers in plasma, dialysate, and breath samples<\/p>\n\n\n\n<p><strong>9)&nbsp;<\/strong>User-centered design and ecosystem engagement, including application design feedback, stakeholder education, and simulation modeling with representative patient cohorts<\/p>\n\n\n\n<p><strong>Results<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>\u00a0 Generate substantial clinical and operational improvements<\/li>\n\n\n\n<li>\u00a0 Automated, multi-parametric, and personalized monitoring of dialysis patients<\/li>\n\n\n\n<li>\u00a0 Scalable solution for global implementation in all hemodialysis patients<\/li>\n\n\n\n<li>\u00a0 Enablement of remote monitoring and home-based dialysis through telemedicine<\/li>\n\n\n\n<li>\u00a0 Improved vascular access management, fewer complications and hospitalizations, better patient outcomes<\/li>\n\n\n\n<li>\u00a0 Enhanced quality of life and reduced healthcare costs through earlier interventions and more accurate treatment \u00a0 delivery<\/li>\n\n\n\n<li>\u00a0 Introduction of new clinical parameters and expanded monitoring capabilities<\/li>\n<\/ul>\n\n\n\n<p><strong>Conclusion<\/strong><\/p>\n\n\n\n<p>SIATE represents a paradigm shift in dialysis treatment,&nbsp;<strong>placing AI at the heart of clinical decision-making<\/strong><\/p>\n\n\n\n<p>The system\u2019s capacity to integrate real-time data from a wide range of sources, apply predictive analytics, and support individualized treatment planning makes it a&nbsp;<strong>powerful tool for improving outcomes in a fragile patient population<\/strong>; its focus on scalability, automation, and telehealth ensures broad applicability across healthcare settings, supporting the move toward&nbsp;<strong>precision nephrology and value-based care<\/strong><\/p>\n","protected":false},"featured_media":27381,"template":"","categoria_progetto":[],"anno_progetto":[],"class_list":["post-25655","progetto_di_ricerca","type-progetto_di_ricerca","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.3.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>SIATE - Gruppo NefroCenter<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.nefrocenter.it\/en\/progetto_di_ricerca\/siate\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"SIATE - Gruppo NefroCenter\" \/>\n<meta property=\"og:description\" content=\"The SIATE project uses Artificial Intelligence (AI) to&nbsp;monitor and personalize hemodialysis therapy in real &nbsp; 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