AIMC Topic: United States

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Transformative potential of artificial intelligence in US CDC HIV interventions: balancing innovation with health privacy.

AIDS (London, England)
Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment through the application of advanced technologies such as machine learning (ML), deep learning (DL), and generative AI (Gen AI). These technologies can ...

End looms for protein contest?

Science (New York, N.Y.)
NIH has not committed to continuing support for contest that inspired AI tools for predicting how proteins would fold.

The association of life's essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007-2018.

BMC pulmonary medicine
OBJECTIVE: Chronic respiratory diseases (CRDs) and cardiovascular diseases (CVD) share common risk factors and frequently co-occur, leading to poorer outcomes. Life's Essential 8 (LE8), a novel metric for cardiovascular health, may provide insights i...

Using Natural Language Processing to Describe the Use of an Online Community for Abortion During 2022: Dynamic Topic Modeling Analysis of Reddit Posts.

JMIR infodemiology
BACKGROUND: Abortion access in the United States has been in a state of rapid change and increasing restriction since the Dobbs v Jackson Women's Health Organization decision from the US Supreme Court in June 2022. With further constraints on access ...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

PloS one
BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subphenotypes of HTN may improve our understanding of its underlying mechanisms and guide more precise t...

Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data.

Scientific reports
Neonatal mortality poses a critical challenge in global health, particularly in low- and middle-income countries. Leveraging advancements in technology, such as machine learning (ML) algorithms, offers the potential to improve neonatal care by enabli...

Identifying and characterising asthma subgroups at high risk of severe exacerbations using machine learning and longitudinal real-world data.

BMJ health & care informatics
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.

GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women.

The international journal of behavioral nutrition and physical activity
BACKGROUND: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and da...

The case for homebrew AI in diagnostic pathology.

The Journal of pathology
Artificial intelligence (AI) methods for digital pathology have tremendous potential to improve cancer diagnostics, biomarkers, and ultimately patient care. These AI methods, if marketed and sold, require authorisation or clearance as in vitro diagno...