Find out more information about the project here.

AI for Everyone is also available for purchase as a paperback edition at cost price here.

Author:
M Arifur Rahman, Hawai‘i Pacific University

Introduction:
This research paper examines the potential benefits of introducing an AI-enhanced pregnancy monitoring system in Bangladesh to enhance maternal health outcomes. Currently, the monitoring of pregnant women in Bangladesh lacks systematic approaches, and many women face limited access to such services due to various factors. Implementing personalized and continuous AI-enhanced monitoring for pregnant women has the potential to improve their health outcomes, but it necessitates access to significant amounts of data. While the Electronic Health Record/Electronic Medical Record (EHR/EMR) system is considered the ideal method for recording healthcare data, Bangladesh has yet to establish a universal EHR system. Although the country has plans to implement an EHR system by 2025, the process is time-consuming. This study assesses the existing maternity healthcare infrastructure in Bangladesh to identify opportunities for integrating AI and proposes recommendations for the government to introduce AI-enhanced pregnancy monitoring systems to address the identified challenges. The research methodology involves identifying technical challenges, gaps in the current technical infrastructure, and drawing lessons from previous project implementations for incorporating AI into pregnancy monitoring. However, as EHR serves as the foundational element for AI-enhanced healthcare, and establishing a universal EHR represents a significant IT undertaking, this study also examines major IT projects carried out by the Bangladesh government, identifies strengths and weaknesses, and provides recommendations for the next steps in EHR development, ultimately leading to AI-enhanced maternity health monitoring systems.

Read this article for more information about the AI for Social Good project and the research in Bangladesh.

Authors:
Olivia Jensen, National University of Singapore
Nathaniel Tan, National University of Singapore
Cornelius Kalenzi, KAIST

Introduction:
Maternal health metrics in Bangladesh improved greatly from the 1990s but the rate of progress has stalled in more recent years and further efforts are now needed to support the health of expecting and new mothers. Artificial Intelligence (AI) has the potential to transform some aspects of healthcare, opening the way for personalised medicine and treatment plans, accelerating diagnosis, drug discovery and development and raising the efficiency of service delivery to reduce costs and maximize the use of available resources. The applications of AI in relation to maternal health are just beginning to be explored but may hold potential to improve health outcomes for this high priority population group. This study provides a high-level assessment of the potential of AI applications to contribute to meeting maternal health objectives in Bangladesh, taking into account the country’s digital technology readiness, the acceptability of AI technologies to user groups and the organizational structure of antenatal care (ANC) services in Bangladesh.

Read this article for more information about the AI for Social Good project and the research in Bangladesh.

Find out more about the paper and its related projects at https://www.apru.org/our-work/pacific-rim-challenges/digital-economy/.

For more information about the Transformation of Work in the 21st Century in Asia Pacific Project, please visit https://apru.org/our-work/pacific-rim-challenges/digital-economy/transformation-of-work/.

AI for Everyone is also available for purchase as a paperback edition at cost price here.

Please see a project overview and policy statement here.
Find out more details about the project here.

Author:
Jasper Tromp, National University of Singapore

Introduction:
Thailand’s digital health landscape is evolving with efforts to embrace technology and leverage its potential benefits. The country has been making strides in digital health readiness, as reflected in its ranking of 59th globally in the Government AI Readiness Index 2021 and 9th in East Asia. However, several barriers and challenges exist in the digital health space.

One of the primary challenges is the fragmented nature of healthcare service provision, affecting differences in data architecture, standards, and collection. Manual data management and the persistence of paper-based electronic health record systems also limit efficient data sharing and interoperability. Limited resources pose a significant barrier, with uneven human, technical, and financial resource distribution across healthcare institutions. High hardware and software acquisition, installation, and maintenance costs further impede engagement in quality data collection and sharing, particularly for smaller clinics and hospitals. Thailand faces a lack of understanding of the value of data and the importance of data security and privacy. Health literacy issues and confusion around data-sharing parameters also contribute to the challenges. Additionally, the absence of precise data-sharing regulations and guidelines at the political and policy levels creates uncertainty and hampers progress.

While Thailand has made progress in its digital health landscape, addressing barriers related to data integration, standardization, resource allocation, and regulations is crucial to unlocking digital health initiatives’ full potential and achieving improved healthcare outcomes.

Read this article for more information about the AI for Social Good project and the research in Thailand.

For more information about the AI for Social Good Summit, please visit here.

To know more about the project, view the webpage.