Biography
Dr. Khondaker A. Mamun
Professor
Dept. of Computer Science and Engineering, United International University
Director - AIMS Lab
Founder and Chairman, CMED Health Ltd.
Title
Building Digital Health Ecosystem towards Developed Bangladesh
Abstract
Healthcare is a basic need of humans. However, it is one of the biggest challenges in Bangladesh and many developing countries, where many people are not getting good healthcare due to lack of infrastructure, systems and resources. On the other hand, healthcare is about to enter a period of rapid transformation by utilizing Fourth Industrial Revolution (4IR) technologies. Longevity and the advance of new technologies and discoveries – as well as innovative combinations of existing ones – are among the many factors pushing patient empowerment, which is fundamentally changing how we prevent, diagnose and cure diseases. Rapid growth of digital technology plays a big role in the healthcare system and helps to predict future health consequences and utilize preventive measures to protect it and improve quality of living. The Digital Health Ecosystem triggered by a fusion of technologies that is blurring the lines between the physical, digital and biological spheres. The potential for merging physical, digital and biological systems certainly has far-reaching potential for healthcare provision. The talk will discuss the way forward of building Digital Health Ecosystem towards Developed Bangladesh. It also discusses the implementation experience of Digital Health Inclusion that is transforming the healthcare landscape in Bangladesh using comprehensive multi-layered scalable digital Healthcare platform by connecting people with health services, early diagnosis, health education & referrals for intervention to achieve Health Inclusion (UHC).
Biography
Khondaker A. Mamun received his Ph.D. in Computer and Medical Engineering from University of Southampton, UK. After that he worked as a Postdoctoral Research Fellow in the PRISM Lab with joint appointment from Institute of Biomaterials and Biomedical Engineering (IBBME), University of Toronto, Toronto, Canada and Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada. Since October 2014, he is working as an Associate Professor and then Professor of Digital Health and Data Science at the Department of Computer Science & Engineering, United International University (UIU), Dhaka, Bangladesh.
Prof. Mamun is the Founder and Director of Advanced Intelligent Multidisciplinary Systems Lab (AIMS Lab) at UIU, where his team actively performs research on the applications of 4IR technologies like, artificial intelligence, big data and internet of things in healthcare, disabilities, brain computer interface (BCI) and education. He has published more than 150 peer reviewed international journal and conference articles. He has invented and implemented a number of digital healthcare and rehabilitations service delivery model and mobile based solutions for developing countries. He also hold a number of patents. His research and innovation have also been featured in a number of local and international news outlets including New Scientist and BBC. His contribution in the innovation and sustainable development is recognized internationally and by the government of Bangladesh. Currently, Prof. Mamun is leading 15+ national and international research projects in his lab.
Prof. Mamun is the founder of (CMED Health), a startup that commercialized from research of AIMS Lab, UIU and focuses on health inclusion through digital healthcare platform. CMED Health is currently serving over 3 million people in Bangladesh and working to attain SDG 3 through achieving universal health coverage (UHC). CMED Health is the winner of National ICT Award 2017 and 2019; APICTA Award 2019 (Vietnam); Bangladesh Business Innovation Award 2018 and 2019; DBS-NUS Social Innovation Award 2018 (Singapore); SeedStarWorld Global Innovation Award 2018 (Switzerland); Startup Challenge 2017, and GP Accelerator 2016 Award. He also received National ICT Award 2017 and APICTA Award 2017 for Autism Barta (Smart Phone App for Autism Screening) and Bolte Chai (Smart Phone App for enhancing communications for nonverbal children). In April 2022, he received an Award from Honorable PM of Bangladesh for his contributions to Autism.He is the organizer and general chair of the first medical engineering conference, MediTec 2016 (International Conference of Medical Engineering, Health Informatics and Technology) in Bangladesh supported by IEEE EMBS. He is also the organizer and chair of the first and second International Neuroscience School (IBRO APRC 2017 and 2019) to develop future neuroscience researcher in Bangladesh, sponsored by International Brain Research Organization (IBRO). With the IBRO support, Prof. Mamun has introduced first Deep Brain Stimulation surgery for Parkinson’s patients in Bangladesh in collaboration with National Institute of Neuroscience and Hospital and Prof. Tipu Z. Aziz, University of Oxford, UK. Prof. Mamun is also the contributor and topic driver of WHO/ITU Focus Group on AI for Health (FG-AI4H), Technical Working Group member and contributor for developing Digital Health Strategy 2020-2025 for the Government of Bangladesh. He designed and developed GP model for urban and rural setting to establish functional referral system for Bangladesh. He is also worked as a national consultant for Unicef, ADB and World Bank on building Digital Health Ecosystem under Ministry of Health and Family Welfare, Government of Bangladesh.
Biography
Dr Mohammad Ali Moni
Senior Research Fellow
School of Health and Rehabilitation Sciences
The University of Queensland, Australia
Title
Wearable Devices and Deep Learning Models for Patient Monitoring and Diagnosis
Abstract
There are many chronic diseases that need continuous monitoring and diagnosis by a clinical expert. The patients often need to carry on with rehabilitation treatment for a quite long time and uninterrupted assessment and monitoring by a clinical expert is required to measure the patient’s condition. So, a patient needs frequent visits to a diagnostic or therapy centre which is very challenging for the patient living in remote and rural areas. This type of continuous monitoring is often complicated, prone to error, costly, and nearly impossible for patients in remote areas. Many of these issues can be resolved by utilising wearable sensors, mobile apps and employing deep learning (DL) based AI methods to assess the patient’s status automatically. Moreover, if the clinical outcome of any treatment measure can be assessed, the subsequent therapeutic decision-making becomes much easier and more effective. Therefore, automated and precise AI techniques for chronic disease patients’ diagnosis, recovery assessment and monitoring could facilitate better management and accurate outcome estimation.
Utilising multimodal data including accelerometers, neuroimaging (MRI & fMRI), EEG and clinical measures we are working to develop AI-based models to collect, store and analyse data from the human body to the cloud using MIoT-enabled wearable sensors as well as automated AI-based monitoring, assessment and decision support system. Finally, utilising all of these multi-sources and multi-modal data we will develop an AI-based operational method that will offer a feasible and cost-effective means for intelligent rehabilitation through smart monitoring and a clinical decision support system. This approach can potentially improve survival and life quality for people in a developing country.
Biography
Dr Mohammad Ali Moni is a Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep leaning models to increase the performance and transparency of Artificial Intelligence (AI) decision-making.
Dr Moni holds a PhD in Artificial Intelligence & Digital Health Data Science in 2015 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, Univrsity of Sydney Vice-chanchellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined at UQ in 2021.
His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving human explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including strokes MRI/fMRI imaging, real time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. Hi research interest includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data especially medical image, neuroimaging, EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.