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Mar 28, 2023

Last Posted: Mar-28-2023 08:23:53

Tracking the Impact of the All of Us Research Program: The All of Us Reports and Publications Database
M Clyne et al, CDC Blog Post, March 28, 2023 Brand

The All of Us Reports and Publications Database (AofURPD) is a continuously updated, searchable database referencing and linking to peer reviewed journal publications, preprint records, as well as select information from websites and media sources that relate to the All of Us Research Program. This blog provides a baseline overview of the content of the AofURPD as of March 17, 2023, including reports and publications as far back as the All of Us Research Program inception in 2016.

Will ChatGPT transform healthcare?
et al. Nature medicine 2023 3 (3) 505-506

Large language models, such as ChatGPT, use deep learning (DL) to reproduce human language in a convincing and human-like way. They are becoming increasingly common and are already being used in content marketing, customer services and a variety of business applications. As a result, it is inevitable that language models will also soon debut in healthcare, an area where they hold tremendous potential to improve health and enhance patients’ lives, but not without pitfalls.

AI-Generated Medical Advice-GPT and Beyond.
Claudia E Haupt et al. JAMA 2023 3

This Viewpoint surveys the medical applications of GPT and related technologies and considers whether new forms of regulation are necessary to minimize safety and legal risks to patients and clinicians. These risks depend largely on whether the software is used to assist health care practitioners or to replace them, and the degree to which clinicians maintain control.

Harnessing the Promise of Artificial Intelligence Responsibly.
David A Dorr et al. JAMA 2023 3

Recent reviews show that nearly all algorithms still fail to achieve substantial gains over human performance when implemented widely and are often based on limited evidence. The development and use of AI algorithms in health care require careful consideration of ethical frameworks relevant to health care and biomedicine, professional oaths and standards, and the systems in which they are implemented.

Laboratory perspectives in the development of polygenic risk scores for disease: A points to consider statement of the American College of Medical Genetics and Genomics (ACMG).
Honey V Reddi et al. Genetics in medicine : official journal of the American College of Medical Genetics 2023 3 100804

This Points to Consider document will (1) provide general consideration for PRS-based genetic tests, (2) outline considerations for the laboratory implementing such tests, (3) recommend appropriate criteria for reporting of PRS, and (4) define and disclose the scope and limitations of such tests.

Prognostic Mutational Signatures of NSCLC Patients treated with chemotherapy, immunotherapy and chemoimmunotherapy.
Margaret R Smith et al. NPJ precision oncology 2023 3 (1) 34

Different types of therapy are currently being used to treat non-small cell lung cancer (NSCLC) depending on the stage of tumor and the presence of potentially druggable mutations. However, few biomarkers are available to guide clinicians in selecting the most effective therapy for all patients with various genetic backgrounds. To examine whether patients’ mutation profiles are associated with the response to a specific treatment, we collected comprehensive clinical characteristics and sequencing data from 524 patients with stage III and IV NSCLC.

Effectiveness of artificial intelligence screening in preventing vision loss from diabetes: a policy model.
Roomasa Channa et al. NPJ digital medicine 2023 3 (1) 53

We designed the Care Process for Preventing Vision Loss from Diabetes (CAREVL), as a Markov model to compare the effectiveness of point-of-care autonomous AI-based screening with in-office clinical exam by an eye care provider (ECP), on preventing vision loss among patients with diabetes. The estimated incidence of vision loss at 5 years was 1535 per 100,000 in the AI-screened group compared to 1625 per 100,000 in the ECP group, leading to a modelled risk difference of 90 per 100,000. The base-case CAREVL model estimated that an autonomous AI-based screening strategy would result in 27,000 fewer Americans with vision loss at 5 years compared with ECP.

Determinants of COVID-19 vaccine fatigue.
Tanja A Stamm et al. Nature medicine 2023 3

Our results suggest that vaccination campaigns should be tailored to subgroups based on their vaccination status. Among the unvaccinated, campaign messages conveying community spirit had a positive effect (0.343, confidence interval (CI) 0.019–0.666), whereas offering positive incentives, such as a cash reward (0.722, CI 0.429–1.014) or voucher (0.670, CI 0.373–0.967), was pivotal to the decision-making of those vaccinated once or twice. Among the triple vaccinated, vaccination readiness increased when adapted vaccines were offered (0.279, CI 0.182–0.377), but costs (-0.795, CI -0.935 to -0.654) and medical dissensus (-0.161, CI -0.293 to -0.030) reduced their likelihood to get vaccinated.


Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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Disclaimer: Articles listed in Hot Topics of the Day are selected by the CDC Office of Genomics and Precision Public Health to provide current awareness of the scientific 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 Clips, 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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