In this paper, we walk you through our challenges, successes, and experience while participating in a Global Health Outreach Project at the University College Hospital (UCH) Ibadan, Nigeria. The scope of the project was to install a Picture Archive and Communication System (PACS) to establish a centralized viewing network at UCH's Radiology Department, for each of their digital modalities. Installing a PACS requires robust servers, the ability to retrieve and archive studies, ensuring workstations can view studies, and the configuration of imaging modalities to send studies. We anticipated that we might experience hurdles for each of these requirements, due to limited resources and without the availability to make a site visit prior to the start of the project. While we ultimately experienced delays and troubleshooting was required at each turn of the install, with the help of dedicated volunteers both on and off-site and the UCH staff, our shared goal was accomplished.
Background
This review aims to describe existing evidence on the state of hypertension in Pakistan, including the prevalence, associated risk factors, preventive strategies, and challenges in the management of hypertension.
Methods
A comprehensive literature search was conducted electronically using PubMed and Google Scholar. Using specific screening methodology, 55 articles were selected to be included.
Results
We found from this extensive review that several small studies report high prevalence of hypertension but there is a lack of population based prevalence of hypertension in Pakistan. Lifestyle risk factors such as obesity, unhealthy diet, decreased physical activity, low socioeconomic status, and lack of access to care were the main associated factors with hypertension. Lack of blood pressure monitoring practices and medication non-adherence were also linked to uncontrolled hypertension in Pakistan and were more evident in primary care setups. The evidence presented is essential for delineating the burden of the disease, hence allowing for better management of this underserved population.
Conclusion
There is a need for updated surveys to depict the true prevalence and management of hypertension in Pakistan. Cost-effective implementation strategies and policies at the national level are needed for both prevention and control of hypertension.
We demonstrate that Domain Invariant Feature Learning (DIFL) can improve the out-ofdomain generalizability of a deep learning Tuberculosis (TB) screening algorithm. It is well known that state of the art deep learning algorithms often have difficulty generalizing to unseen data distributions due to ''domain shift.'' In the context of medical imaging, this could lead to unintended biases such as the inability to generalize from one patient population to another. We analyze the performance of a ResNet-50 classifier for the purposes of TB screening using the four most popular public datasets with geographically diverse sources of imagery. We show that without domain adaptation, ResNet-50 has difficulty in generalizing between imaging distributions from a number of public TB screening datasets with imagery from geographically distributed regions. However, with the incorporation of DIFL, the out-of-domain performance is greatly enhanced. Analysis criteria includes a comparison of accuracy, sensitivity, specificity and AUC over both the baseline, as well as the DIFL enhanced algorithms. We conclude that DIFL improves generalizability of TB screening while maintaining acceptable accuracy over the source domain imagery when applied across a variety of public datasets.INDEX TERMS Tuberculosis, X-ray imaging, domain adaptation, domain invariant feature learning, generative adversarial networks, deep learning, computer vision, computer aided diagnosis, DIFL.
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