AIMC Topic: United States
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Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.
PloS one
Jul 9, 2025
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
Jul 7, 2025
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
Jul 7, 2025
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
Jul 6, 2025
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
Jul 4, 2025
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...
The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.
Lipids in health and disease
Jul 3, 2025
BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒glucose index, a marker of insulin resistance, and the composite indicator of obesity.
Construction and validation of a risk prediction model for chronic obstructive pulmonary disease (COPD): a cross-sectional study based on the NHANES database from 2009 to 2018.
BMC pulmonary medicine
Jul 3, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major global public health concern, and early screening and identification of high-risk populations are critical for reducing the disease burden. Although several studies have explored the...
Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.
BMC public health
Jul 3, 2025
Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globally due to its high incidence, disability, and mortality rates. Accurate identification of CMM patterns is crucial for CMM classification and health m...
Spatial analysis of county-level determinants of overdose mortality in the United States using spatial machine learning.
BMC public health
Jul 2, 2025
In recent years, there has been a growing body of literature on identifying effective determinants for modeling the spatial variation of overdose rates, addressing this emerging public health concern globally. We compiled a range of widely recognized...
Assessment of drug induced hyperuricemia and gout risk using the FDA adverse event reporting system.
Scientific reports
Jul 2, 2025
Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also play a role. However, their specific risks and mechanisms remain inadequately studied. Disproportiona...
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