AIMC Topic: California

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Social Media Recruitment in Indigenous and Native American Populations: Challenges in the AI Age.

JMIR public health and surveillance
Using social media recruitment for public health research presents both opportunities and challenges. Despite its increased use, few studies have detailed the practical issues, challenges encountered, and alternative strategies available for social m...

Fire risk to structures in California's Wildland-Urban Interface.

Nature communications
The destructive impacts of wildfires on people, property and the environment have dramatically increased, especially in the Wildland-Urban Interface (WUI) in California. In these areas structures are threatened by both approaching flames and lofted e...

Racial and ethnic disparities in exposure to short-term NO air pollution in California during 1980-2022.

Journal of hazardous materials
Historical racial and ethnic disparities in short-term exposure to ambient nitrogen dioxide (NO) have rarely been investigated, primarily due to the lack of spatiotemporally resolved NO data covering the historical period. In this study, we used publ...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

Environmental health perspectives
BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contributor to the rise in ASD cases. This study investigated how the risk of ASD associated with prenatal...

Machine learning for monitoring per- and polyfluoroalkyl substance (PFAS) in California's wastewater treatment plants: An assessment of occurrence and fate.

Journal of hazardous materials
Wastewater treatment plants (WWTPs) are significant sources of per- and polyfluoroalkyl substances (PFAS) pollution, but comprehensive monitoring and management are impractical and cost-prohibitive. To strengthen monitoring programs, we developed mac...

Use of natural language processing method to identify regional anesthesia from clinical notes.

Regional anesthesia and pain medicine
INTRODUCTION: Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within indi...

Physician Perspectives on Ambient AI Scribes.

JAMA network open
IMPORTANCE: Limited qualitative studies exist evaluating ambient artificial intelligence (AI) scribe tools. Such studies can provide deeper insights into ambient AI implementations by capturing lived experiences.

Extracting Housing and Food Insecurity Information From Clinical Notes Using cTAKES.

Health services research
OBJECTIVE: To assess the utility and challenges of using natural language processing (NLP) in electronic health records (EHRs) to ascertain health-related social needs (HRSNs) among older adults.

Optimizing multi label student performance prediction with GNN-TINet: A contextual multidimensional deep learning framework.

PloS one
As education increasingly relies on data-driven methodologies, accurately predicting student performance is essential for implementing timely and effective interventions. The California Student Performance Dataset offers a distinctive basis for analy...

A Deep Learning Based Framework to Identify Undocumented Orphaned Oil and Gas Wells from Historical Maps: A Case Study for California and Oklahoma.

Environmental science & technology
Undocumented Orphaned Wells (UOWs) are wells without an operator that have limited or no documentation with regulatory authorities. An estimated 310,000 to 800,000 UOWs exist in the United States (US), whose locations are largely unknown. These wells...