CONSULT: Collaborative Mobile Decision Support for Managing Multiple Morbidities
Lead Research Organisation:
King's College London
Department Name: Informatics
Abstract
The provision of healthcare to people with long-term conditions is a growing challenge, which is particularly acute for the growing proportion of the UK population that suffers from multiple morbidities.
Research has established that involving patients in the management of their own disease has long-term health benefits. Advances in wireless sensor technology means that it is practical for patients to monitor a wide range of health and wellness data at home, including blood pressure, heart function and glucose levels, without direct supervision by medical personnel. The advent of smart phone technologies, appearing widely throughout the nation's population, enables the exciting possibility of putting state-of-the-art intelligent decision-support systems into the hands of the general public.
However, such sensor data is currently disconnected both from the patient context, provided by the Electronic Health Record, and from the treatment plan, based on current best-evidence guidelines and customised by the patient's GP. In cases of multi-morbidities, there is no clear strategy for combining multiple guidelines into a coherent whole. Furthermore, personalised treatment plans are rigid and do not dynamically adapt to changes in a patient's circumstances. Finally, the record of patient condition and decisions made is not routinely captured in a standardised way, preventing learning from feedback about treatment effectiveness.
To address these problems, CONSULT will combine wireless "wellness" sensors with intelligent software running on mobile devices, to support patient decision making, and thus actively engage patients in managing their healthcare. Our software will use computational argumentation to help patients follow treatment guidelines and will learn details specific to individuals, personalising treatment advice within medically sound limits. Critically, the software will detect conflicts in treatment guidelines that frequently arise in the management of multiple morbidities. The software will provide advice regarding which treatment options to follow, when the conflicts can be resolved by the patient and when a resolution requires an intervention from a clinician. The software will thus help patients handle routine maintenance of their conditions, while ensuring that medical professionals are consulted when appropriate. This will enable patients to take charge of their own conditions, while being fully supported in both traditional and new ways. By routinely capturing the data provenance of the recommendations made, actions taken and the resulting patient progress, the software will provide valuable insights into the effectiveness of treatments and underlying guidelines in multi-morbidity scenarios.
The technology will be evaluated across multiple dimensions in a proof-of-concept study, engaging stroke patients, their carers and medical professionals, while capitalising on King's College London's world-leading position in stroke research and its established patient groups, particularly those connected to the South London Stroke Register programme.
Helping patients to govern their own care will reduce the demands made on medical professionals, while reaping the health benefits of self-management. Integrating live information from monitoring devices will make it possible to distinguish between situations that need attention from medical professionals, and those that do not, reducing the number of extra appointments that patients and doctors need to schedule. Using live information will also make it possible to detect changes in the course of a disease, allowing pre-emptive actions to be taken, and thus reducing the amount of time that someone suffering from a long-term condition may have to spend in hospital. Overall, our approach will not only provide more efficient care, but also allow care to be better tailored to the needs of each individual.
Research has established that involving patients in the management of their own disease has long-term health benefits. Advances in wireless sensor technology means that it is practical for patients to monitor a wide range of health and wellness data at home, including blood pressure, heart function and glucose levels, without direct supervision by medical personnel. The advent of smart phone technologies, appearing widely throughout the nation's population, enables the exciting possibility of putting state-of-the-art intelligent decision-support systems into the hands of the general public.
However, such sensor data is currently disconnected both from the patient context, provided by the Electronic Health Record, and from the treatment plan, based on current best-evidence guidelines and customised by the patient's GP. In cases of multi-morbidities, there is no clear strategy for combining multiple guidelines into a coherent whole. Furthermore, personalised treatment plans are rigid and do not dynamically adapt to changes in a patient's circumstances. Finally, the record of patient condition and decisions made is not routinely captured in a standardised way, preventing learning from feedback about treatment effectiveness.
To address these problems, CONSULT will combine wireless "wellness" sensors with intelligent software running on mobile devices, to support patient decision making, and thus actively engage patients in managing their healthcare. Our software will use computational argumentation to help patients follow treatment guidelines and will learn details specific to individuals, personalising treatment advice within medically sound limits. Critically, the software will detect conflicts in treatment guidelines that frequently arise in the management of multiple morbidities. The software will provide advice regarding which treatment options to follow, when the conflicts can be resolved by the patient and when a resolution requires an intervention from a clinician. The software will thus help patients handle routine maintenance of their conditions, while ensuring that medical professionals are consulted when appropriate. This will enable patients to take charge of their own conditions, while being fully supported in both traditional and new ways. By routinely capturing the data provenance of the recommendations made, actions taken and the resulting patient progress, the software will provide valuable insights into the effectiveness of treatments and underlying guidelines in multi-morbidity scenarios.
The technology will be evaluated across multiple dimensions in a proof-of-concept study, engaging stroke patients, their carers and medical professionals, while capitalising on King's College London's world-leading position in stroke research and its established patient groups, particularly those connected to the South London Stroke Register programme.
Helping patients to govern their own care will reduce the demands made on medical professionals, while reaping the health benefits of self-management. Integrating live information from monitoring devices will make it possible to distinguish between situations that need attention from medical professionals, and those that do not, reducing the number of extra appointments that patients and doctors need to schedule. Using live information will also make it possible to detect changes in the course of a disease, allowing pre-emptive actions to be taken, and thus reducing the amount of time that someone suffering from a long-term condition may have to spend in hospital. Overall, our approach will not only provide more efficient care, but also allow care to be better tailored to the needs of each individual.
Planned Impact
Chronic health conditions are widespread in the UK. NHS England estimates that around 15 million people in England (30% of the population) suffer from chronic health conditions. In Scotland and Wales, the proportion of the population affected is even higher. Such conditions require constant management, and they account for 50% of all GP appointments and 64% of all outpatient appointments. With careful monitoring, it is possible for those who are chronically ill to lead high-functioning lives and to have their care managed at home. However, many chronic conditions can easily lead to hospital stays, with the result that 70% of all inpatient bed days are required to treat the chronically ill. The prevalence of chronic conditions is closely correlated with age. For example, 14% of those younger than 40 report a long-term condition, compared with 58% of those over 60. With an ageing population nationwide, dealing with chronic conditions will consume even more resources in the future.
The number of people with more than one chronic disease is also growing. It is predicted that there will be 2.9 million people with two or more long-term conditions by 2018, an increase of one million since 2008. Such multiple morbidities are difficult to navigate because traditionally each disease has been managed separately, so drug regimes and treatment plans are developed in isolation and may conflict with each other. This growth in multiple morbidities presents a further challenge to our healthcare system: by 2018, dealing with them will cost GBP 5 billion more than in 2011.
A key feature of our proposed CONSULT approach is that it goes far beyond what is possible with medical advice web sites. By adopting a collaborative approach based on integrating wellness sensor data with a patient's electronic health record (EHR), it is possible to provide personalised care in home settings, reducing the amount of hospital and GP time required, and improving treatment outcomes. By specifically targeting the issues that arise in handling multiple morbidities, our approach aims to help the most vulnerable members of the chronically ill population.
Specifically, our research will impact several categories of stakeholders:
* Patients will be assisted in the management of their conditions. Our work will literally put up-to-date information and support at their fingertips. Our goal is to help patients sort through what is relevant to them, understand their options, avoid information overload and make the best decisions, even when treatment guidelines conflict. By engaging patients in this way, we aim to help them obtain the health benefits that have been shown for the chronically ill who self-manage their treatment. Overall, our approach offers both economic benefits, reducing the cost of long-term care, and social benefits in terms of increased quality of life.
* Carers will be empowered in the management of patients with chronic conditions. Our work will provide live support and connection to their patients, and the added security of knowing that medical professionals will be informed of any relevant changes in patients' conditions.
* Clinicians' efforts will be better apportioned. Since wellness sensor data will be integrated into the EHR, clinicians will be able to monitor patients' conditions without bringing them into clinic, and receive alarms when there are situations that require immediate attention.
In addition, medical researchers will be able to obtain integrated data from sensors and EHRs to conduct observational studies on efficiency of treatments and accuracy of measurements in the home setting. The provenance of data collected, backing decision support, will enable commissioning bodies to gain unique insight into the efficiency and cost-effectiveness of treatments. Technology will also impact commercial decision-support providers looking to deliver collaborative home care solutions.
The number of people with more than one chronic disease is also growing. It is predicted that there will be 2.9 million people with two or more long-term conditions by 2018, an increase of one million since 2008. Such multiple morbidities are difficult to navigate because traditionally each disease has been managed separately, so drug regimes and treatment plans are developed in isolation and may conflict with each other. This growth in multiple morbidities presents a further challenge to our healthcare system: by 2018, dealing with them will cost GBP 5 billion more than in 2011.
A key feature of our proposed CONSULT approach is that it goes far beyond what is possible with medical advice web sites. By adopting a collaborative approach based on integrating wellness sensor data with a patient's electronic health record (EHR), it is possible to provide personalised care in home settings, reducing the amount of hospital and GP time required, and improving treatment outcomes. By specifically targeting the issues that arise in handling multiple morbidities, our approach aims to help the most vulnerable members of the chronically ill population.
Specifically, our research will impact several categories of stakeholders:
* Patients will be assisted in the management of their conditions. Our work will literally put up-to-date information and support at their fingertips. Our goal is to help patients sort through what is relevant to them, understand their options, avoid information overload and make the best decisions, even when treatment guidelines conflict. By engaging patients in this way, we aim to help them obtain the health benefits that have been shown for the chronically ill who self-manage their treatment. Overall, our approach offers both economic benefits, reducing the cost of long-term care, and social benefits in terms of increased quality of life.
* Carers will be empowered in the management of patients with chronic conditions. Our work will provide live support and connection to their patients, and the added security of knowing that medical professionals will be informed of any relevant changes in patients' conditions.
* Clinicians' efforts will be better apportioned. Since wellness sensor data will be integrated into the EHR, clinicians will be able to monitor patients' conditions without bringing them into clinic, and receive alarms when there are situations that require immediate attention.
In addition, medical researchers will be able to obtain integrated data from sensors and EHRs to conduct observational studies on efficiency of treatments and accuracy of measurements in the home setting. The provenance of data collected, backing decision support, will enable commissioning bodies to gain unique insight into the efficiency and cost-effectiveness of treatments. Technology will also impact commercial decision-support providers looking to deliver collaborative home care solutions.
Publications
Kökciyan N
(2019)
A Collaborative Decision Support Tool for Managing Chronic Conditions.
in Studies in health technology and informatics
Bikakis Antonis
(2021)
JOINT ATTACKS AND ACCRUAL IN ARGUMENTATION FRAMEWORKS
in JOURNAL OF APPLIED LOGICS-IFCOLOG JOURNAL OF LOGICS AND THEIR APPLICATIONS
Ford E
(2019)
Public Opinions on Using Social Media Content to Identify Users With Depression and Target Mental Health Care Advertising: Mixed Methods Survey.
in JMIR mental health
Cohen A
(2018)
A characterization of types of support between structured arguments and their relationship with support in abstract argumentation
in International Journal of Approximate Reasoning
Tapuria A
(2021)
Impact of patient access to their electronic health record: systematic review.
in Informatics for health & social care
Kokciyan N
(2021)
Applying Metalevel Argumentation Frameworks to Support Medical Decision Making
in IEEE Intelligent Systems
Sklar E.I.
(2018)
Explanation through argumentation
in HAI 2018 - Proceedings of the 6th International Conference on Human-Agent Interaction
Ganzer-Ripoll J
(2018)
Combining Social Choice Theory and Argumentation: Enabling Collective Decision Making
in Group Decision and Negotiation
Kokciyan N.
(2018)
Reasoning with metalevel argumentation frameworks in aspartix
in Frontiers in Artificial Intelligence and Applications
Kökciyan N.
(2018)
Privacy-preserving intersection management for autonomous vehicles
in CEUR Workshop Proceedings
Cyras K.
(2018)
Argumentation for explainable reasoning with conflicting medical recommendations
in CEUR Workshop Proceedings
Kökciyan N.
(2018)
Towards an argumentation system for supporting patients in self-managing their chronic conditions
in CEUR Workshop Proceedings
Wang W
(2022)
Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study
in BMC Neurology
Ford E
(2021)
Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners.
in BMC medical informatics and decision making
Sassoon I
(2018)
A formalisation and prototype implementation of argumentation for statistical model selection
in Argument & Computation
Sassoon I
(2021)
Argumentation schemes for clinical decision support
in Argument & Computation
Massa TB
(2023)
Fusel oil reaction in pressurized water: characterization and antimicrobial activity.
in 3 Biotech
Description | One of the key questions that this combined project aimed to answer is whether it is technically possible to carry out remote monitoring of patients using commercial (rather than custom built) wellness sensors. We completed a successful pilot study in which the software system that we developed monitored individuals for a week, tested with a small group of university students (n=6). This pilot study ended just before the first Covid lockdown and demonstrated the technical feasibility. A more extensive study with stroke patients was promised in the proposal but has been delayed, initially by Covid and subsequently by issues with changes to the ethics (due to Covid-induced changes to the protocol), and changes to the third-party APIs of the commercial wellness devices that we are using. We are still working towards completing the study, supported by the University of Lincoln. |
Exploitation Route | Our work so far has developed a software system which can collect and collate data from wireless wellness sensors, and present this to individuals along with advice on what action to take, and explanations for why these actions are recommended and explanations for what their data is showing. Users can interrogate the explanations if they are unsure what the answers mean. This work has been focused on stroke patients, but could be applied to any healthcare application for which wireless monitoring devices exist, and, indeed, to other domains which make use of such sensors. We are investigating applications in social care, and in the agri-food domain. The latter, in particular, seems to be a promising avenue. |
Sectors | Agriculture Food and Drink Digital/Communication/Information Technologies (including Software) Healthcare Leisure Activities including Sports Recreation and Tourism |
URL | https://consultproject.co.uk/ |
Description | Working with colleagues in the Lincoln Institute for Agrifood Technology, we have identified several businesses in the agritech sector which might benefit from the application of the argumentation mechanisms at the heart of the CONSULT project. We are working with them to find ways to use the technology to support decision makers in agriculture make explainable decisions in cases where there are complex tradeoffs between different courses of action, such as decisions about treatments that will have impacts on both yield and environmental sustainability that need to be balanced. Since these are small companies (typically agritech startups), we are looking to fund this work through Innovate UK but have yet to be successful. |
First Year Of Impact | 2022 |
Sector | Agriculture, Food and Drink |
Impact Types | Economic |
Description | Developing and implementing Machine Learning driven analytics for quality improvement in healthcare |
Amount | £337,149 (GBP) |
Funding ID | 707135 |
Organisation | The Health Foundation |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 02/2018 |
End | 09/2021 |
Description | London Substantive Site for HDR UK |
Amount | £6,000,000 (GBP) |
Organisation | Health Data Research UK |
Sector | Private |
Country | United Kingdom |
Start | 03/2018 |
End | 03/2023 |
Description | REFLECT: Wearable sensors for personalised decision support |
Amount | £55,564 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start |
Description | Collaboration with Masaryk University, Czech Republic on non-repudiation of provenance |
Organisation | Masaryk University |
Country | Czech Republic |
Sector | Academic/University |
PI Contribution | Through King's work, provenance templates have by now become a recognised methodology for the construction of data provenance records. Each template defines the provenance of a domain-specific action in abstract form, which may then be instantiated as required by a single service call to the provenance template server. As data reliability and trustworthiness becomes a critical issue in an increasing number of domains, there is a corresponding need to ensure that the provenance of that data is non-repudiable. This can be achieved by using a third-party trusted notary to store supporting evidence of the data provenance being recorded. In collaboration with Masaryk Unviersity, we developed two new, complementary modules to our template model and implementation to produce non-repudiable data provenance. The first, a module that traces the operation of the provenance server itself, and records a provenance trace of the construction of an object-level document, at the level of individual service calls. The second, a non-repudiation module that generates evidence for the data recorded about each call, annotates the server trace accordingly, and submits a representation of that evidence to a provider-agnostic notary service. We also contributed use cases developed from the decision support projects we are working on, namely EPSRC CONSULT and ROAD2H. |
Collaborator Contribution | Masaryk University contributed their expertise in the developing ISO TC 276 standard and previous non-repudiation work (outside of the provenance template domain). |
Impact | The main output so far is a paper that will be submitted to Provenance Week 2020, and an expanded version to FGCS journal. The paper evaluates the applicability of our approach in the context of a clinical decision support system (e.g. EPSRC CONSULT and ROAD2H). We first demonstrate the suitability of our solution with respect to a security threat model for such an environment. We then select three use cases from within the system with contrasting data provenance recording requirements and analyse the subsequent performance of our prototype implementation against three different notary providers. The work will also feed in into the work ISO TC276 WP6 working group that Curcin, Fairweather, Holub, and Wittner are all members of. |
Start Year | 2020 |
Description | Collaboration with National Institute for Health and Care Excellence on use of provenance for managing recommendations and evidence |
Organisation | National Institute for Health and Care Excellence (NICE) |
Country | United Kingdom |
Sector | Public |
PI Contribution | My team is applying the Provenance Template modeling method to the challenges that NICE has in managing their research metadata. Specifically, they are interested in exploring the versioning of their guideline recommendations, and its relationship to the changing evidence base. |
Collaborator Contribution | NICE is conducting a survey of their stakeholders (industrial partners, clinical organizations etc.) to understand their needs with respect to data provenance of NICE guidelines. This is a valuable piece of work that they are uniquely positioned to deliver, and will be of significant use to my team in developing the provenance research portfolio further. As a secondary benefit, the NICE employee placed in my group is advising on the ROAD2H and CONSULT projects which both have elements of guideline modeling, to ensure its applicability to the UK national requirements. |
Impact | We have jointly obtained the "Towards Computable Guidelines", MRC Industry Proximity Award funding worth £30K, to establish a pilot collaboration through hosting a NICE employee in my group, and are currently working on a paper and a larger grant proposal. This is a multi-disciplinary collaboration that spans informatics and public health. |
Start Year | 2017 |
Title | A Microservice Architecture for Computer-Interpretable Guidelines |
Description | As a part of the CONSULT project, we have developed a new microservice architecture design pattern for the construction of guideline processing tools. This architecture has successfully been used to redesign the guideline processing tool developed by Zambolini et al. [1], and this new software is currently being used by the ROAD2H project at Imperial College London, and will ultimately be used in CONSULT itself. [1] Zamborlini, Veruska, et al. "Inferring recommendation interactions in clinical guidelines 1." Semantic Web 7.4 (2016): 421-446. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | The tool is currently being used by researchers at Imperial College as part of the EPSRC - Global Challenges Research Fund project Road2H (http://www.road2h.org/) |
URL | https://github.com/consult-kcl/drug-interaction |
Title | Nokia Health Middleware |
Description | Middleware designed to improve interactions with the Nokia Health API, and thus Nokia Health devices. |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | None as yet. |
URL | https://github.com/consult-kcl/nokia-health |
Title | Software for "An argumentation-based approach for generating domain-specific explanations" |
Description | The software is an implementation of the EvalAF and ExpAF algorithms introduced in "An argumentation-based approach for generating domain-specific explanations" with a running example that also appears in the paper. |
Type Of Technology | Webtool/Application |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | None as yet. |
URL | https://git.ecdf.ed.ac.uk/nkokciya/explainable-argumentation |
Title | Software for "Applying Metalevel Argumentation Frameworks to Support Medical Decision Making" |
Description | This is an implementation of the metalevel argumentation systems from the paper in Aspartix. This includes a metalevel extension to Aspartix. |
Type Of Technology | Webtool/Application |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | None as yet. |
URL | https://git.ecdf.ed.ac.uk/nkokciya/metalevel-aspartix |
Title | Software for "Argumentation Schemes for Clinical Decision Support" |
Description | This software is an implementation of the argument schemes described in the paper "Argumentation Schemes for Clinical Decision Support". |
Type Of Technology | Webtool/Application |
Year Produced | 2021 |
Open Source License? | Yes |
Impact | None as yet |
URL | https://git.ecdf.ed.ac.uk/nkokciya/arg-aimed20 |
Description | CONSULT presentation to Guys and St Thomas's Trust NIHR Biomedical Research Centre Analytical Cluster |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | A presentation of CONSULT technology for integrating wearable data and Electronic Health Record technology for stroke patient decision support was given to the Analytics cluster of the GSTT NIHR BRC. The audience feedback was very positive and several areas in GSTT hospital settings were identified to potentially pilot the CONSULT technology in follow-up projects. |
Year(s) Of Engagement Activity | 2019 |
Description | MEDRACER18 workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The talks and papers in MEDRACER focussed mainly on the representation of, and reasoning with, clinical guidelines. Martin Chapman was invited as the representtive of the CONSULT project, and spoke about the work done so far on deriving treatment plans from abstract guidelines, which involves using argumentation to resolve any contradictions within those guidelines based on patient preferences. |
Year(s) Of Engagement Activity | 2018 |
URL | https://sites.google.com/view/medracer |
Description | Meeting at University of Michigan, Ann Arbor, to set the Learning Health System agenda for decision support |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Funded by the Gordon and Betty Moore Foundation to envision a Learning Health System for diagnostic excellence, University of Michigan held a one-day expert meeting to design and propose in more detail socio-technical infrastructure components for an LHS focused on diagnosis. Vasa Curcin was invited as the UK/European representative to the workshop, bringing in the experiences from CONSULT and ROAD2H. |
Year(s) Of Engagement Activity | 2019 |
Description | Presentation to Society for Academic Primary Care (SAPC) South East conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | One of the project team members gave a talk about the project at the Society for Academic Primary Care (SAPC) South East conference. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.phpc.cam.ac.uk/pcu/sapcse2020/ |
Description | Presentation to the Clinical Research Network South London, Stroke Specialty Group |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | The CRN South London Stroke Specialty Group brings together researches and medical professionals engaged in research around stroke. At the meeting on 10th January 2018, Dr Talya Porat gave a presentation to the group about the aims of the CONSULT project. |
Year(s) Of Engagement Activity | 2018 |
Description | Presentation to the London Argumentation Workshop |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | One of the team members, Dr Isabel Sassoon, gave a presentation on the computational argumentation component of CONSULT, the core technology at the heart of the decision support system, to a group of London-based argumentation researchers. |
Year(s) Of Engagement Activity | 2019 |
Description | Talk to the Petnica Science Camp students in Serbia |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Schools |
Results and Impact | Presentation on data provenance and the Learning Health System given to 120-odd high school students attending the Petnica Science Camp in Serbia. The talk coincided with the summer term at PSC, and the students present there were all involved in their own research projects. The presentation kick-started a longer discussion on the role of data provenance in alleviating privacy fears around how people's private medical data are being used. |
Year(s) Of Engagement Activity | 2017 |
Description | The International Workshop on Dialogue, Explanation and Argumentation for Human-Agent Interaction (DEXAHAI) at the 24th European Conference on Artificial Intelligence |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was an academic workshop focused on approaches, concepts and applications relevant to supporting dialogue and explainability in intelligent software that interacts with people. These are key areas for CONSULT, and following the good response we obtained to the previous event, we decided to organize another iteration of the workshop. As before the aim of the event, which was achieved, was to discuss key issues for CONSULT with an international set of participants, learn what other researchers are doing, and gain feedback on our work. |
Year(s) Of Engagement Activity | 2020 |
URL | https://sites.google.com/view/dexahai-at-ecai2020/ |
Description | The International Workshop on Dialogue, Explanation and Argumentation for Human-Agent Interaction (DEXAHAI) at the International Conference on Human-Agent Interaction |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This was an academic workshop focused on approaches, concepts and applications relevant to supporting dialogue and explainability in intelligent software that interacts with people. Since these are key areas for CONSULT, we decided to organize an event at which we could discuss them with an international set of participants, learn what other researchers are doing, and gain feedback on our work. |
Year(s) Of Engagement Activity | 2018 |
URL | https://sites.google.com/view/dexahai-18/home |
Description | Tutorial at 18th International Conference on Autonomous Agents and Multiagent Systems. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Members of the project team, along with a colleague from the University of Aberdeen, presented a tutorial "Computational Argumentation in the Context of Human-Agent Interaction", on the core technology at the heart of what we are developing for CONSULT, at the 18th International Conference on Autonomous Agents and Multiagent Systems. The audience was drawn from the conference attendees, primarily doctoral students, but also researchers in the field. |
Year(s) Of Engagement Activity | 2019 |
URL | https://sites.google.com/view/arg-hai-tutorial-aamas19/home |
Description | Tutorial at 24th European Conference on Artificial Intelligence |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Members of the project team, along with a colleague from University of Aberdeen, presented a tutorial "Computational Argumentation in the Context of Human-Agent Interaction", on the core technology at the heart of what we are developing for CONSULT, at the 24th European Conference on Artificial Intelligence. The audience was drawn from the conference attendees, primarily doctoral students, but also researchers in the field. |
Year(s) Of Engagement Activity | 2020 |
URL | https://sites.google.com/view/arg-hai-tutorial-ecai20/ |
Description | Tutorial at Computational Models of Argument Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | This was a tutorial on "Argumentation-based Dialogue" for PhD students attending the Computational Models of Argument conference. This conference has an associated "Summer School on Argumentation", and the tutorial was a part of that. |
Year(s) Of Engagement Activity | 2020 |
URL | https://ssa2020.dmi.unipg.it/program.html |
Description | Tutorial at Human Agent Interaction Conference 2018. |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Members of the project team, along with colleagues from King's and the University of Aberdeen, presented a tutorial "Computational Argumentation in the Context of Human-Agent Interaction", on the core technology at the heart of what we are developing for CONSULT, at the 6th Annual International Conference on Human-Agent Interaction. The audience was drawn from the conference attendees, primarily doctoral students, but also researchers in the field and at least one journalist. |
Year(s) Of Engagement Activity | 2018 |
URL | http://hai-conference.net/hai2018/programme/tutorial/ |
Description | Visit to Erasmus MC, Rotterdam, to present ProvTemp outputs |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Vasa Curcin and Martin Chapman visited Rotterdam to present the data provenance and CONSULT technologies developed in the group to the researchers at Erasmus MC. The specific goal was to see how our provenance template server could be used to provide reproducible features to the tooling around OHDSI Observational Medicines Outcome Partnership's Common Data Model. Several possibilities were identified and we shall aim to submit a joint proposal around it. |
Year(s) Of Engagement Activity | 2019 |
Description | Visit to Mayo Clinic in Scottsdale, AZ |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Martin Chapman visited Adela Grando (https://chs.asu.edu/adela-grando) at the Mayo Clinic in Scottsdale, AZ. The discussion focussed on her current work, which, like CONSULT, involves promoting self-management, but instead for diabetic patients, who are fitted with blood glucose monitors (https://www.researchgate.net/publication/325884737_Design_and_Testing_of_a_Smartphone_Application_for_Real-Time_Self-Tracking_Diabetes_Self-Management_Behaviors). Additionally, we looked into some work she has been doing on logging clinicians' workflows with EHRs, with the aim of supporting clinicians in moving between EHR software provided by different vendors (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371265/) which bears direct relevance to the technologies developed in our group. |
Year(s) Of Engagement Activity | 2018 |