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Last Posted: Mar 20, 2023
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Medicine and health of 21st Century: Not just a high biotech-driven solution.
Assidi Mourad et al. NPJ genomic medicine 2022 11 (1) 67

Although the potential of biotechnology is motivating, we should not lose sight of approaches that may not seem as glamorous but can have large impacts on the healthcare of many and across disparate population groups. A balanced approach of “omics and big data” solution in contemporary health systems along with a large scale, simpler, and suitable strategies should be defined with expectations properly managed.

Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.
Gao Chengcheng et al. NPJ digital medicine 2022 10 (1) 161

With the recent prevalence of COVID-19, cryptic transmission is worthy of attention and research. Early perception of the occurrence and development risk of cryptic transmission is an important part of controlling the spread of COVID-19. Previous relevant studies have limited data sources, and no effective analysis has been carried out on the occurrence and development of cryptic transmission. Hence, we collect Internet multisource big data (including retrieval, migration, and media data) and propose comprehensive and relative application strategies to eliminate the impact of national and media data.

Big data and AI in pandemic preparedness
The Lancet Summit: October 27-28, 2022

Managing COVID-19 and infectious disease is a global priority over the next few decades. Clinical and research communities are committed to reviewing the global response to the COVID-19 pandemic and a key part has been the unprecedented use and rapid scale of technology. This conference will allow diverse stakeholders to discuss opportunities for new pandemic warning systems based on modelling approaches using AI; advances in real-world surveillance and tracking of disease spread; AI for drug screening and rapid diagnostics; and advances in remote treatment and telehealth.

Big data in basic and translational cancer research.
Jiang Peng et al. Nature reviews. Cancer 2022 9

Fast data growth has given rise to an evolving concept of ‘big data’ in cancer, whose analysis demands large computational resources and can potentially bring novel insights into essential questions. Indeed, the combination of big data, bioinformatics and artificial intelligence has led to notable advances in our basic understanding of cancer biology and to translational advancements.

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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