TL;DR:
- NSU and UNC jointly organized a certificate course on “Machine Learning for Maternal Health” at the NSU campus.
- Renowned experts discussed the applications of machine learning in improving maternal healthcare.
- Dr. Javed Mostafa highlighted the importance of using machine learning to predict pregnancy risks and emphasized the need for proper data banking on health issues in Bangladesh.
- A demonstration showcased the practical application of machine learning and cloud-based data management in healthcare.
- Dr. Hasan Mahmud Reza emphasized the significance of machine learning in improving maternal health in Bangladesh.
- Shamim Ahmed emphasized the importance of cloud-based data management and privacy in machine learning applications.
- The event saw active participation from senior faculty members and public health experts, ensuring a fruitful learning experience for all participants.
Main AI News:
A groundbreaking collaboration between the NSU School of Health Science and the University of North Carolina (UNC), Chapel Hill, USA, has resulted in a prestigious certificate course titled “Analytics & Machine Learning Techniques for Maternal and Health Interventions.” This highly anticipated event took place on July 17, 2023, at the NSU campus, drawing together a distinguished group of experts and professionals from the field of maternal healthcare.
Leading the discourse at this remarkable gathering was Dr. Javed Mostafa, a renowned Professor at the University of North Carolina and the esteemed Director of the Carolina Health Informatics Program. Dr. Mostafa delivered a captivating keynote address, underscoring the immense potential of machine learning in predicting pregnancy risks and providing early counseling to mitigate adverse incidents. He emphasized the need to effectively harness vast amounts of data to unlock the full potential of machine learning tools.
Dr. Mostafa shed light on the state of the US healthcare system for pregnant women, using it as a reference point to highlight the importance of developing comprehensive health informatics in Bangladesh. He emphasized the necessity of establishing robust data repositories to facilitate the integration of machine learning in maternal care, with the ultimate goal of reducing the maternal death rate in the country.
During an interactive session, Kibria from UNC demonstrated a cutting-edge machine learning pipeline utilizing cloud computing. This insightful demonstration showcased the practical application of these technologies and shed light on the immense potential of cloud-based data management in healthcare. The presentation also addressed the pertinent concerns surrounding data privacy in the realm of machine learning.
Dr. Hasan Mahmud Reza, the esteemed Dean of the School of Health and Life Sciences, underscored the significance of machine learning in the context of healthcare in Bangladesh. Expressing concern over the shortage of qualified medical practitioners in rural areas, Dr. Reza posited that machine learning could play a pivotal role in bridging this gap and improving maternal health outcomes across the country.
Shamim Ahmed, the CEO of InNeed Intelligent Cloud, brought attention to the crucial importance of cloud-based data management and the associated privacy issues within the realm of machine learning applications. His valuable insights contributed to the comprehensive understanding of the audience regarding the practical implications of these technologies.
The day-long event saw the active participation of senior faculty members from NSU and esteemed public health experts. Guiding the proceedings with finesse and expertise were the skillful moderators Nibras and Razmin from UNC, ensuring a highly productive and enriching learning experience for all the participants.
Conclusion:
The collaboration between NSU and UNC to host the certificate course on “Machine Learning for Maternal Health” signals the growing importance of machine learning in revolutionizing maternal healthcare. The event highlighted the potential of machine learning tools in predicting pregnancy risks and improving the overall quality of care for pregnant women. The focus on developing proper data banking and cloud-based data management underscores the need for comprehensive health informatics in Bangladesh. This presents significant opportunities for market players in the healthcare sector to leverage machine learning techniques and cloud-based solutions to enhance maternal healthcare outcomes, ultimately contributing to a healthier future for pregnant women in the country.
