In addition to the scientific results derived from the execution of the project’s randomized clinical trial, that will assess the effectiveness of an AI-based, patient self-empowerment and PoC support platform, BD4QoL will produce new exploitable technologies underpinning such platform, that may successfully enter the market of mHealth medical devices and applications.
BD4QoL domain ontology for head and neck cancer and health-related quality of life, that maps not only medical data but also PREM/PROM questionnaires, behavioural and sentiment / affective traits data into health and quality of life indicators. The ontology will be an open access resource available for research purposes.
he mobile data collection modules and apps represent the “edge-computing” components of the BD4QoL system integrating the data collection and pre-processing modules from mobile phones embedded sensors and localization apps, the patients empowerment interface, the PREM/PROM questionnaires and user's consent and preferences setting. The apps will be available for Android and iOS.
The BD4QoL counselling e-coach chatbot and the natural language understanding algorithms for sentiment analysis and interactive patients' support, relying on IBM Watson algorithms for natural language understanding and reinforcement learning techniques for adaptive and personalized counselling and alerts generation.
he BD4QoL data management infrastructure, relying on secure and privacy preserving cloud services, and the relevant API for data access and data management and analysis. Theinfrastructure is designed to be exported to open science cloud systems for data and open access tools reuse in research environments.
The data interpretation and visualization dashboard to inform clinical decision making and personalized patients' support, relying on BD4QoL adaptive Workflow Management System designed to personalized data presentation to the different stakeholders involved in patients’ follow up.
Multidimensional deep learning-based risk prediction and risk stratification models for Health Related Quality of Life and late sequelae and early detection models, mixing traditional and novel sources of data and implementing breakthrough techniques for Hybrid Activity Recognition, Deep Learning for sequence modelling and algorithms for time-series analysis, that will be released for open research.
Extended "Big Data" dataset on head and neck cancer clinical, behavioural and quality of life-related data, collected from more than six thousands patients from Italy and UK that will be available along with BD4QoL trials results for new research
First in the art integrated occupational and medical datasets for the identification of impacts of having a head and neck tumor on work- and health-related outcomes.
Novel approaches for clinical trials protocols design, involving data from mobile apps and artificial intelligence algorithms, compliant with new CTTI and SPIRIT-AI guidelines, opening new paradigms in clinical research.
Guidelines for the integration of cancer patients' quality of life indicators and point-of-care data into the regional personal health record folder resulting from pilot integration in Lombardy Region.
