Search

In this deliverable, we describe the knowledge engineering process used to formalize the clinical practice guidelines implemented in CAPABLE. More precisely the following steps will be illustrated: Choice of the guidelines - selecting the most compatible guidelines for the system. Text processing mechanism - detecting recommendations and translating them into a set of computer-interpretable rules. Analysis of each recommendation - detecting what raw data type was involved, which vocabulary is mostly suitable for coding, and what abstractions need to be performed on this raw data. This allows for achieving clearer representation, at the same time producing reusable pieces of knowledge. The detected raw data also represents the minimum data set needed by the CAPABLE DSS (Decision Support System), so this step has been fundamental for the development of other CAPABLE components. Translation of each recommendation into a set of computer-interpretable rules, organization of rules into a logical flow, and their representation using the Composer tool, i.e., the authoring tool developed by one of the project partners. In this step, adaptations have been implemented to allow smooth guideline implementation in different healthcare settings. Validation of the represented knowledge by simulating realistic clinical scenarios (oncologists have been involved in this phase). Particular attention has been put to multimorbidity management, since running guidelines for different pathologies may lead to contradictory recommendations, which must be resolved Handover to the implementation team and refinement iterations with the team itself. The deliverable will then provide the actual description of the formalized guidelines, through a set of flowcharts, and links to their representation in Composer., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

This deliverable shares the results of the third usability and user experience study of the CAPABLE prototypes as defined in previous deliverable D7.1. During these activities, the ongoing developed interfaces of the final system provided by WP6 have been evaluated by applying the two methods described in D7.1: Interviews with patients. These interviews gathered feedback from the end users of the Patient App: Melanoma and Kidney cancer patients during the treatment phase. Considering the broader applicability of the app to any type of cancer patient, this iteration also included other types of oncological patients, and cancer survivors (treatment finished in no more than 2 years). Overall, 17 patients have been interviewed. Interviews with healthcare professionals (HCPs). These interviews aimed to collect overall feedback about both doctors’ and patients’ solutions, understand if the clinical and patients’ needs are covered, and revise the core functionalities that have been proposed in the current prototype. A total of 10 health professionals have been interviewed. The protocols of each study are attached in the Annex. The document also presents the general conclusions from these validation activities and the next steps to follow in future developments to satisfy the user experience needs emerging in this process. Differently from the previous two rounds, the current pandemic situation allowed all the interviews to be performed in a presence. The following tools have been used: Online survey engine based on Limesurvey, used for the interviewer as a guide. Online access to the clinical dashboards to inspect functionalities for the Health Care Professionals. App installed on an Android device to test the functionalities for the patients. An Asus Vivowatch 5 smartwatch., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

The aim of this deliverable is to define the requirements of the CAPABLE system. These requirements include clinical requirements regarding the clinical scope of decision-support and its content (knowledge base), patient and clinician user needs, and technical system requirements for the different system components. Following our iterative development approach for the CAPABLE system, this document presents the functional and non-functional requirements. This document opens with a literature review (Section 2, corresponding to Task T2.1) that we have performed to identify the state of the art of data-science-based methods and systems for supporting the quality of life of cancer patients, starting with data collection and data integration methods, and continuing to machine-learning-based prediction models and patient coaching systems. The literature review allowed us to identify best practices that we plan to adopt in the CAPABLE system, as well as open challenges, many of which we plan to address. Going from the state of the art to our own CAPABLE system, in Section 3 we present the overall system architecture, along with the different components of the system. In addition to this structural description of the system, we also provide a workflow presenting the process of care supported by the CAPABLE system, from patient enrollment and initial setup of the physician-facing dashboard and patient-facing mobile app, to the ongoing services provided by the systems to these users, including patient monitoring and decision-support. The following chapters present a description of the methods that we used to collect different requirements, as well as the requirements themselves. Section 4 presents patient requirements (Task T2.1) and Section 5 ��� clinical requirements (Task T2.3), relating to the needs of the clinicians as well as a selection of clinical practice guidelines, monitoring data to be collected by patients at home, and certification/barriers to market. Section 6 (corresponding to Task T2.6) starts with a set of Sequence Diagrams that specify how the system components interact with each other in order to achieve the M12 Demo Scenario. Then we present all functional and non-functional requirements of the different system components (Data integration components [Case Manager, Data Platform, and the Knowledge-Data Ontology Mapper (KDOM)], decision-support [Computer-interpretable Guideline (CIG) Execution Engine and Knowledge Base, Multimorbidity Controller, Coaching System ��� all three rely on the existing decision model of the PROforma formalism], user interfaces [Patient APP GUI, Doctor APP GUI], sensors) as well as security/privacy). Section 7 presents the Technical requirements for data representation, integration, quality, and exchange (corresponding to Task T2.4). Section 8 presents the Technical requirements for the AI data processing and analysis methods (corresponding to Task T2.5), including predictive model and knowledge discovery (pattern detection). Technical detailed requirements for security and privacy will be formulated in WP4. WP2 continued to meet in Year 2 to complete the formulation of requirements. Issues that were elaborated in Year 2 include defining the structure and content of the pdf summary for the general practitioners [Section 4, Req. 5.3.1], additional requirements related to security by design [Section 6.12], and the final choice of phones and sensors [Section 6.8]. Based on feedback from the M12 Demo from all stakeholders and on the 1st technical review, we added one requirement [Req 4.5] and elaborated the user interface screens and for all requirements related to the clinicians' app and the patients' app [Sections 4.7 and 5.9]., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

The aim of this deliverable is to describe a framework which is part of the CAPABLE system architecture. A framework is defined as a set of concepts, libraries, tools, practices, and analytic methodologies. In this document, we focus on the artificial intelligence (AI) framework, while we consider AI in a broad notion that covers formal knowledge representation and logic-based reasoning, as well as machine learning techniques. This document describes the means by which the AI framework supports the requirements of melanoma and renal cancer patients, their caregivers, and physicians., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

This deliverable analyzes and describes the requirements for establishing an infrastructure for CAPABLE that adheres to the Findability, Accessibility, Interoperability, Reusability (FAIR) Principles, with a focus on the data-related functionality. Hence, it describes the required functionality to adhere to the FAIR Principles. This analysis results in recommended implementation decisions for FAIR-enabling functionality. This functionality is to be provided through the Application Programming Interfaces (APIs) of the CAPABLE components, and enables access to metadata, access to data, and data access control., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

The document shows the activities of market research performed in the second half of the first year of the project. Differently from the initial deliverable (D8.1): the focus of the market research has been to study the specific costs of kidney and melanoma cancer, and the possible barriers and success criteria to market to then continue the CAPABLE roadmap to the adoption following the CEHRES method presented in D8.1. The document also presents an update of the technology vigilance, which also contains a specific selection of solutions that are relevant competitors of CAPABLE and a study of the existing solution in the 2 hospitals of CAPABLE (ICSM and NKI-NVL). The document also presents an updated version of the Consortium IPR strategy and questionnaire interviews to be launched next year to start exploiting interests from key decision makers., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

The aim of this deliverable is to define the requirements of the CAPABLE system. These requirements include clinical requirements regarding the clinical scope of decision-support and its content (knowledge base), patient and clinician user needs and requirements, and technical system requirements for the different system components. Following our iterative development approach for the CAPABLE system, this document presents the majority of the functional and non-functional requirements. Once we implement the system in iterations and have users try out the system, additional requirements may be refined and reported at the end of Year 2., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052

This document presents the results of the second evaluation and validation iteration of theCAPABLE prototypes as defined in previous deliverable D7.1.In this validation process, an updated version of the WP6 prototype has been evaluated applying the two methods presented in D7.1: Interviews with patients and relatives. These interviews aimed to collect feedback from the end-users of the Patient App: melanoma and kidney cancerpatients during the treatment phase. Given the broader applicability of the app toany type of cancer patient, this iteration included also other types of oncologicalpatients, cancer survivors (treatment finished since no more than 2 years), andexperts in patients’ needs, such as caregivers. Overall, 17 patients and 2 caregivershave been interviewed. Interviews with healthcare professionals (HCPs). These interviews aimed tocollect overall feedback about both doctors’ and patients’ solutions, understand ifthe clinical and patients’ needs are covered, and revise the core functionalities thathave been proposed in the current prototype. A total of 11 health professionalshave been interviewed. We present the results of the 2 executedstudies. The protocols of each study are attached in the annex. The document also presentsthe general conclusions from these validation activities and the next steps to follow in thefuture developments in order to satisfy the user experience needs found in this process.

This document presents the results of the second evaluation and validation iteration of the CAPABLE prototypes as defined in previous deliverable D7.1. In this validation process, an updated version of the WP6 prototype has been evaluated applying the two methods presented in D7.1: Interviews with patients and relatives. These interviews aimed to collect feedback from the end-users of the Patient App: melanoma and kidney cancer patients during the treatment phase. Given the broader applicability of the app to any type of cancer patient, this iteration included also other types of oncological patients, cancer survivors (treatment finished since no more than 2 years), and experts in patients��� needs, such as caregivers. Overall, 17 patients and 2 caregivers have been interviewed. Interviews with healthcare professionals (HCPs). These interviews aimed to collect overall feedback about both doctors��� and patients��� solutions, understand if the clinical and patients��� needs are covered, and revise the core functionalities that have been proposed in the current prototype. A total of 11 health professionals have been interviewed. We present the results of the 2 executed studies. The protocols of each study are attached in the annex. The document also presents the general conclusions from these validation activities and the next steps to follow in the future developments in order to satisfy the user experience needs found in this process., This deliverable is a part of a project receiving funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 875052