Date: 31st March 2021
(12:30 to 15:30 Pakistan Standard Time)
Deadline for Registration: 29th March, 2021
Organised by COMSTECH in collaboration with IEEE Educational Activities Karachi Section
Overview
The pandemic opens new dimensions of thinking in every walk of life, especially our healthcare industry which now requires new ways of working, new methods of communication, finding new solutions to problems and trying to innovate the solutions. Digital health in the current era is more than just on-line (virtual) visits and distant patient monitoring. The COVID-19 pandemic primarily redesigned the health care system and highlighted the important gaps that can be problematic in the future. Healthcare workers have to re-think the architectural models and we have to move in a maintainable way.
Realizing the importance of the challenges in the healthcare systems, COMSTECH has planned a one-day seminar focusing on the subject in March 2021.
Objective
The objective of this International seminar is to bring together the researchers, industrial partners, and practitioners interested in the specification, design, and development of smart healthcare systems that will improve personal healthcare in a better way.
Key Contents
- Smart healthcare
- Patient Tracking
- Intelligent based Services
- Remote Health Monitoring
- Reported Attacks
Target Audience
Healthcare professionals, students, researchers, young entrepreneurs and policymakers from the OIC countries are encouraged to apply.
Registration Process
Step 1: Open online registration form
Step 2: Read instructions in the application form carefully and submit a properly filled form.
Step 3: Selected candidates will be notified through email; hence, applicants are required to check their emails regularly.
SPEAKERS DETAILS
Prof Andrew Ware
Professor
University of South Wales
Talk Title: COVID-19: A Personal Impact Assessment
Abstract: The period 2020-21 will be remembered as the time that the world simultaneously slowed down and speeded up. Coronavirus has meant that for most of the last year much of the world’s population have had their movements and activities restricted. People have been confined to their home, and anyone showing symptoms of the virus have been instructed to self- isolate. At the same time ‘working from home’ has, for many, become the norm. This new normal has acted as a fillip for the progress of technology that enables remote connectivity. Change in the way we work, rest, and play have been necessitated at lightning speed. The past twelve months have highlighted the need for digital inclusion. While many have benefited from the life of the new normal, others have been significantly disadvantaged. As we, hopefully, move beyond COVID, the mantra of many World leaders is to “build back better, build back greener.” What might that look like in reality? How can we all benefit from the collective learning of the experience of the last? These are big questions, and the answers are far beyond a single individual. However, what the talk aims to do is present the contribution of one individual based on their experience to the great debate.
Andrew Ware
Andrew is Professor of Computing at the University of South Wales in the United Kingdom. His research interest centers on the use of intelligent computer systems (Artificial Intelligence and Data Science oriented solutions) to help solve real-world problems. Prof. Andrew is currently working on AI-related projects with several industrial and commercial partners that include Tata Steel, National Health Service Wales Informatics Service, and Wye Education. In addition, Andrew is Director of Aurora International Consulting Ltd-an innovative software-as-a-service company that provides AI-enabled review software to the construction industry. Andrew is also the Director of Research for the Welsh Institute of Digital Information, a collaboration between the University of South Wales, the University of Wales Trinity Saint David, and the NHS Wales Informatics Service (NWIS). Furthermore, Andrew is a Regional Director of Techno Camps- an innovative and ambitious project that seeks to engage young people with computing and its cognate subjects. Moreover, Andrew is Editor in Chief of the journal Annals of Emerging Technologies in Computing (AETiC).
Maurice Mulvenna
Professor of Computer Science
Ulster University Artificial Intelligence Research Centre
Talk Title:Digital Mental Health and Wellbeing Interventions: Analyzing Interactions from apps, Conversational User Interfaces and Telephony Helplines
Abstract: Research on the analysis of data for digital health interventions in health and wellbeing has historically been used to aid in usability analysis, user adoption/retention analysis or to reveal usage patterns in using technology. Research has also been carried out to explore how rehabilitation devices can have data or event logging incorporated, but this has been more to support the goal of device monitoring. More recent research has examined engagement data in web-based intervention platforms but has primarily focused on the visualization of user log or user event data.
Digital phenotyping is the term given to the capturing and use of user log data from health and wellbeing technologies used in apps and cloud-based services. Digital phenotyping was originally proposed as a way to correlate a person’s mental state by using their metadata and even sensor data on their smartphone. In some cases, the data is physiological, for example pulse or movement-related, and it is collected automatically. In other cases, the data is actually metadata, for example, when a call is made and the call duration rather than the content of the call. Oftentimes, as would be expected from a personal device located on the body of the user, rich data pertaining to geo-location, social media use and interaction is gathered. Health and wellbeing-related, scientifically validated assessment scales may also generate digital phenotype data. Another form of digital phenotype data is the Experience Sampling Method (ESM) (or the Ecological Momentary Assessment or EMA), which originally made use of paper-diary techniques to enable people to record their observations or answers to specific questions and combined the ecological validity with the rigorous measurement techniques of psychometric research. EMA secures data about both behavioral and intrapsychic aspects of individuals’ daily activities, and it obtains reports about the experience as it occurs, thereby minimizing the effects of reliance on memory and reconstruction which can often be impaired by hindsight bias or recall bias.
Mental health helplines generate anonymous digital telephony meta-data comprising date, time, duration of calls which are also amenable to data analysis. The use of digital phenotyping data, telephony meta-data and their analysis using machine learning and artificial intelligence is important since many national public health organizations are exploring how to use digital technologies such as health apps and cloud- based services as digital health interventions for self-management. And logging user interactions allows for greater insight into user needs and provides ideas for improving these digital interventions-for example, through enhanced personalization. Public health services can benefit since the data can be automatically and hence cost-effectively collected. Such data may facilitate new ways for digital epidemiological analyses and provide data to inform health policies. This talk describes the analysis, using machine learning, of digital intervention and helpline telephony data using case studies from each area. In clinical practice, Ativan is used in the fight against alcohol and drug withdrawal syndrome, as well as for the symptomatic treatment of neuropsychiatric disorders. Benzodiazepines affect inhibitory neurotransmitter receptors by increasing their affinity for gamma-aminobutyric acid (GABA). As a result, the excitability of nerve cells quickly decreases, and the effect of GABA increases.
Maurice Mulvenna
Maurice Mulvenna is serving as a Professor of Computer Science at Ulster University. His research areas include: computing and mental health, artificial intelligence, digital wellbeing, innovation and assistive technologies. He has been a Principal Investigator on around 50% of over 150 international research projects. Arising from his research, he has published over 400 papers and served on numerous program committees.
He was also co-chair of the 32nd British Human-Computer Interaction conference in 2018, and co-chair of both the 31st European Cognitive Ergonomics Conference (ECCE-2019) and the 5th IEEE International Conference on Internet of People (IoP-2019) in 2019. He is a senior member of both the Institute of Electrical and Electronics Engineers and the Association for Computing Machinery, and a chartered fellow of the British Computer Society.
Prof. Jim Buckley.
S. Lecturer, CSIS Department,
University of Limerick
Talk Title: Covigilant: towards optimizing Contact Tracing Apps from user, best-of-breed and idealized perspectives
Abstract: As the COVID-19 pandemic continues into its second year of global disruption, countries who reduce the spread of the SARS-CoV-2 virus are faring better in healthcare outcomes and economic terms. Controlling its spread relies, in part, on “contact tracing” which aims to rapidly identify the close contacts of infected people so that they can be advised to limit their social interactions, and get tested, thereby reducing onward spread of the virus.
Novel Contact Tracing Applications (CTAs) can potentially simplify the laborious work of contact tracing and are thus a tempting prospect, particularly given their ability to identify close-contacts who are unknown to cases and their ability to identify contacts-contacts near instantaneously. But these apps are only as useful as the proportion of the population who download and retain them. Consequently, optimizing these apps is important, particularly from a user perspective, but also based on best-practice as currently embodied in existing apps and based on idealized healthcare/societal thinking, regardless of any technological constraints.
Covigilant is a 6-month, rapid response Covid-19 project funded by the Irish state, towards optimizing Contact Tracing Apps from these perspectives. This talk will discuss the body of work performed in the Covigilant project and its findings. The project has generated 2 journal and 2 conference articles, with three more still in preparation. But more importantly, it has fed the findings directly into the (Irish) Department of Health, and our National Health Service (The HSE) to inform the evolution of the Irish Contact Tracker app (https://covidtracker.gov.ie/), and the national messaging around that app.
Jim Buckley
Jim Buckley is serving as a Professor in CSIS department and as a Principal Investigator in Lero, University of Limerick. He is director of a €6 million research initiative in Trustworthy and Responsible Software Engineering (TREES)-an initiative funded entirely by industry. Furthermore, Prof. Buckley is Leading 4 industry-co-funded research projects, with a combined budget of over €1.3 million: CroSUn (Wood), ETHER (Horizon Globex), C-DAS (Huawei) and FoSOMO (ACI);
He is also the Author/Co-Author on funding with a total value of over €36.5 million to University of Limerick. In addition, Prof. Buckley is a member of the 8-person, SFI expert advisory group on Covid-19 Contact Tracing for the HSE.
Dr. Wasswa William
Senior Lecturer
Mbarara University of Science and Technology
Title: Digital Health in the Era of COVID-19: ‘PapsAI’ use case in Uganda
Abstract: Globally, cervical cancer ranks as the fourth most prevalent cancer affecting women with 527,624 women diagnosed with the disease in 2019 and 265,672 dying from it every year. Over 80% of cervical cancer cases occur in less developed countries of which the highest incidences are in Africa. Over 85% of those diagnosed with the disease in Uganda die from it due to late diagnosis. Today, the delivery of oncology has become very complex, with a heavy reliance on technology, not only for the accurate diagnosis of the patient, but also for the delivery of the agreed treatment and patient follow-up. Pap-smear screening is the most successful and effective attempt by medical science and practice to facilitate the early detection and screening of cervical cancer. However, the manual analysis of the pap-smear images is time-consuming, laborious and error-prone as hundreds of sub-images within a single slide have to be examined under a microscope by a trained cytopathologist who are few in LMIC. In case of a complicated slide, this is manually transported to another expert in another screening center. Patients’ records including pap-smears, next of kin, tumor board meetings data are not stored for follow up.
This research has presented potent digital pathology platform for automated diagnosis and classification of cervical cancer from pap-smear images. The digital pathology platform is in four-fold:
- A low cost microscope slide scanner to produce quick, reliable and high-resolution cervical cell images from pap-smear slides.
- Automated assessment of chances of contacting cervical cancer given cervical cancer risk factors.
- Automated analysis of pap-smear images for diagnosis and classification of cervical cancer from the images.
- AI-powered integrated oncology patients’ information management system with telemedicine support.
For a convectional pap-smear slide of size (25*50) mm, the developed microscope can produce a digital image in less than 5 minutes with resolutions of 1.10µm and 0.42µm using a 10x lens and a 40x lens respectively. The image quality is comparable to high-end commercial microscopes at a cost of less than US$500.
The major contribution of this platform in a cervical cancer screening is that it reduces on the time required by the cyto-technician to screen many slides by eliminating the obvious normal ones, hence more time can be put on the suspicious slides. The oncology information management system has been developed based on a digital health framework developed from this research with end-users central to the design process, and we are optimistic that once integrated into the national cancer screening program, it has potential of improving cancer screening in Uganda leading to reduced deaths from cancer.
Wasswa William
Dr. Wasswa is serving as a senior lecturer at Mbarara University of Science and Technology in the department of Biomedical Sciences and Engineering. He is the head of the department of Biomedical Sciences and Engineering and leads the Advanced Medical Imaging and Artificial Intelligence Lab in the department of Biomedical Sciences and Engineering. Furthermore, he is a member of Mbarara University’s Quality Assurance Committee and Research Ethics Committee; the CEO of Global Auto Systems Ltd Uganda- a startup revolutionizing service delivery with use of AI, Data analytics, Block chain and Robotics.
His research interests include: The Application of Artificial Intelligence, Machine Learning, Modelling & Simulation and Data Science in Health, Agriculture, Business and Education to improve service delivery in low and middle income countries.
Moderator/Coordinator
Dr. M Sadiq Ali khan
Associate Professor
Chair IEEE Educational activities Karachi section
Workshop Coordinator
Muhammad Haris Akram
Programme Manager, COMSTECH
Tel: +92-51-9220681-3
Fax: +92-51-9205264, +92-51-9220265
Email: haris@comstech.org
