This study aimed at summarizing the existing health policies for stateless populations living in the 10 ASEAN countries: Brunei, Cambodia, Lao PDR, Indonesia, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. We followed scoping review method recommended by Arksey and O'Malley. Our inclusion criteria were based on three concepts: populations (stateless and undocumented people), issues (healthcare policies and regulations), and settings (10 ASEAN countries). Our findings suggest that none of the ASEAN countries have explicit healthcare policies for stateless people except Thailand. We also observed that ratification of international human rights treaties relating to the right to health does not necessarily translate into the provision of healthcare policies for stateless population. Although Thailand seems like the only country among 10 ASIAN countries having health policies for stateless populations in the country, the question remains whether having a policy would lead to a proper implementation by ensuring right to health.
Amongst the most common causes of death globally, stroke is one of top three affecting over 100 million people worldwide annually. There are two classes of stroke, namely ischemic stroke (due to impairment of blood supply, accounting for ~70% of all strokes) and hemorrhagic stroke (due to bleeding), both of which can result, if untreated, in permanently damaged brain tissue. The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke management. Abiding to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, we have surveyed a total of 177 research papers published between 2010 and 2021 to highlight the current status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation. This work concludes by showcasing the current requirement of this domain, the preferred modality, and prospective research areas.