NBEC ConferenceNBEC Conference
Senior Principal Assistant Director, Engineering Services Division, MOH
Mr. Jeffry bin Mohammad Noor has acquired more than 18 years of experience in the Biomedical Engineering Industrial field. He received his bachelor’s in electronic engineering from University of Southampton, United Kingdom in 2004. Currently he is attached to the Engineering Services Division Ministry of Health as Senior Principal Assistant Director specializing in Hospital Support Services (HSS) focusing on Biomedical Services. He is experienced with all stages of HSS management at the hospital level and Headquarters level. He possesses a strong background in operational management and customer relations. He is a member of the Professional Affiliation Board of Engineers Malaysia (BEM), Biomedical Engineering Association of Malaysia (BEAM), Institution of Engineers Malaysia (IEM) and Ahli Jawatankuasa Dasar Regulatori Medical Device Authority.
Title : Service Modernisation : Real-time Asset Management and IoT Application in Medical Equipment Maintenance
Digitalization has influenced the finance and manufacturing sector a lot over recent years. Leveraging digital technologies for asset management is the right step because of its data-driven nature. As for the concession company for hospital support services, nearly the fastest development is seen in the digitalization of asset management, i.e., in the acquisition, management, maintenance and procurement of new assets in the most profit-making way possible.
The benefits of going digital are evident (towards green technology). The benefits include faster performance and cheaper operation cost in the context of a growing amount of operations. Digitalization also enables predictive analytics and promote AI which accelerate the decision making and daily operation. Predictive analytics, in its turn, enables experts to make smarter decisions and avoid behavioral bias.
Thus, they earn a greater profit on the assets under management. Clients and end-user have real-time insights into the operation, availability, and usage. Finally, clients and end-user can invest less in back-office operations, leverage cheaper locations, and outsource services.
Public Health Medicine Specialist, National Institutes of Health, MOH
Dr. Fadli Ismail earned his medical degree from Barts and the London, Queen Mary University of London in 2010. After gaining four years of clinical experience in Malaysian hospitals, he joined the Institute for Health Systems Research under the National Institute for Health (NIH) in 2014. Driven by a passion for public health, he pursued further studies in the field, completing his Master of Public Health (MPH) in 2017 and Doctor of Public Health (DrPH) in 2020 from the University of Malaya.
Currently, Dr. Fadli serves as a Public Health Medicine Specialist in the Sector for Biostatistics & Data Repository at the National Institutes of Health, Ministry of Health Malaysia. He is deeply committed to open science and is an active member of the Malaysian Open Science Alliance (MOSA), a national movement under the Akademi Sains Malaysia that promotes open science principles in Malaysia.
Dr. Fadli also plays a crucial role in developing a Big Data Ecosystem for the NIH. He is heavily involved in setting a robust data strategy for the institute, overseeing initiatives such as facilitating cloud computing solutions for researchers working on Big Data projects, establishing the NIH Data Repository System (NIH-DaRS) to curate and reuse primary research data produced in Ministry of Health, and providing training opportunities in big data analytics and Artificial Intelligence.
Coming soon
Head of Biosignal Processing Research Group, UTM
Associate Professor Ir. Dr. Malarvili BalaKrishnan have acquired more than 15 years of experience in the academics as well as involvements in the biomedical industry. She received Doctor of Philosophy (Medical Sciences Engineering) from The University of Queensland, Queensland, Australia in 2008. Currently, she is attached to School of Biomedical and Health Sciences Engineering, Universiti Teknologi Malaysia. She founded Biosignal Processing Research Group (BSP-RG) in 2010 within the faculty to champion the research, development and commercialization of Biomedical Instrumentation. Dr. Malarvili is actively involved in research related to medical monitoring devices that focuses on detection of neonatal seizure, sudden cardiac death, fetal heart rate monitoring , respiratory illness screening device and many more. To date, she has published more than 130 papers. She also received 10 international awards, 16 national awards and many more appreciation certificates. In addition, she has chaired sessions in prestigious conference, editorial board member and technical reviewer by IEEE, EMBS and medical society. She was recently selected for an ‘Outstanding Woman in Health and Medical Sciences’ award at the 4th Venus International Women Awards – VIWA 2019, Chennai, India.
Capnography has been implemented throughout history for detecting airway and pulmonary obstructions in critical care settings. The basic principle of capnography relies on the measurement of carbon dioxide (CO2) and provides details in terms of ventilations and metabolisms in a spontaneously breathing patient. The analysis of capnogram waveforms reveals multiple features and instantly determines the state of breathing. This chapter details the crux of capnography systems for delivering precise capnogram signals in the advancement of Industry 4.0. The chapter outlines the systematic analyses and prospective tools utilized in literature for incorporating capnography in medical facilities. The use of capnography is extensively reviewed to evaluate the current evidence of capnography efficiency. The vital role of capnography for the remote assessment of respiratory condition is discussed. The evolution of Industry 4.0 has broadened the technology for vibrant capnography signal processing with the aim of developing wireless networking in health facilities.
Head of the MMU-UKM-IMU Artificial Intelligence for Digital Pathology Research Excellence Consortium, MMU
Mohammad Faizal Ahmad Fauzi (CEng, SMIEEE, MIEM) received the B.Eng. degree in Electrical and Electronic Engineering from Imperial College, London, UK in 1999, and the Ph.D. degree in Electronics and Computer Science from University of Southampton, Southampton, UK in 2004. He is currently a Professor at the Faculty of Engineering, Multimedia University, and the Head for the MMU-UKM-IMU IMU Artificial Intelligence for Digital Pathology (AI4DP) Research Excellence Consortium. His main research interests are in the area of signal and image processing, pattern recognition, computer vision and medical imaging. From May 2013 to June 2014, he was attached to the Clinical Image Analysis Lab at the Ohio State University, USA where he works on digital histopathology, especially on cancer and diseases analysis. He has published more than 100 journal and conference articles to date.
Title : Towards Personalized Medicine: Automated Scoring of Hormone Receptor for Breast Cancer Treatment Recommendation
Hormone receptor status is determined primarily to identify breast cancer patients who may benefit from hormonal therapy. The current clinical practice for hormone receptor testing, using either Allred score or H-score, is still based on laborious manual counting and estimation of the proportion (P-score) and intensity (I-score) of positively stained cancer cells in immunohistochemistry (IHC)-stained slides. This manual process is not only tedious and time-consuming but is also prone to errors and inaccuracies. In this talk we will present our work in developing an automated system for the scoring of estrogen receptor (ER) biomarkers for breast cancer treatment recommendation. The developed system has the potential to improve the overall standards of prognostic reporting for breast cancer by minimizing errors and inaccuracies, eliminating sampling bias and reader variability, providing faster and more consistent reporting, as well as reducing pathologists’ workload.