## 2 Methods Used for Integrated Monitoring and Management of Diet-Related Diseases
### Tailored Patient-Centric RHMS--RO-SmartAgeing System, NeuroPredict Platform, and HepatoCnect System
#### 2.2.2 NeuroPredict Platform  
The \"Advanced Artificial Intelligence Techniques in Science and Applications\" is a research project started recently, in 2023. One of its objectives is to evolve the NeuroPredict Platform as a key biomedical component. The primary objective of the NeuroPredict Platform is to develop predictive models geared towards the prevention, early detection, and long-term monitoring of individuals with neurodegenerative conditions. These models are intricately linked to a diverse array of medical data and information obtained through nonintrusive intelligent monitoring, alongside clinical data sourced from patients, inclusive of open data repositories. The inception of the NeuroPredict Platform stems from the groundwork laid by the smart remote monitoring environment for the elderly, the RO-SmartAgeing system, which was developed within the overarching project. This environment is meticulously crafted to align with the unique features of neurodegenerative diseases and is supplemented with smart devices tailored to these specific health challenges. The NeuroPredict Platform is underpinned by three key pillars:  
* Comprehensive monitoring of health parameters, ongoing activities, behaviour, and lifestyle through meticulous data collection within a personalized intelligent environment. This encompasses the integration of IoMT devices designed for monitoring health parameters, such as heart rate, electrocardiogram (ECG), blood pressure, pulse, sleep-related metrics, body positioning, bioelectrical impedance analysis, body fat, muscle mass, bone mass, and more. It also encompasses ambient parameters and sensors for motion and physical activity;
* Leveraging of open data sources specifically for neurodegenerative conditions;
* Integration of data and insights derived from established cognitive tests (e.g., Mini-Mental Test Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog)) to formulate predictive models catering to the prevention, early detection, and ongoing monitoring of individuals with neurodegenerative conditions. All amassed data are meticulously stored in a database and subjected to cloud-based AI analyses to pinpoint patterns associated with cognitive status. Data correlated with patients' medical histories and real-time inputs from various IoMT devices will find a repository in the ICIPRO cloud. These data are subsequently transmitted to the specialized AI-driven predictive monitoring platform tailored for patientsdealing with neurodegenerative conditions, facilitating AI algorithms in prognosticating the longitudinal progression of their health. The overarching research endeavours are focused on the establishment of multivariate AI-driven predictive models for neurodegenerative diseases. These models will seamlessly integrate the high-dimensional data aforementioned to adeptly identify, assess, and monitor patients grappling with these conditions. Additionally, the intention is to assimilate select vital parameters measured through (bio)markers identified as particularly predictive for certain neurodegenerative conditions. The data analytics will adopt a longitudinal approach. The NeuroPredict Platform champions a proactive and preventive management approach to neurodegenerative diseases. Drawing from available public information, current estimations posit that Romania lacks a comparably intricate computer system akin to the NeuroPredict Platform. The platform is conceived as a patient-centric, accessible, and minimally invasive tool with the flexibility for customisation based on medical intricacies. Its envisioned deployment spans both patient homes and medical care units.