AIMC Topic: California
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Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.
Environmental health perspectives
Jun 12, 2025
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...
Use of natural language processing method to identify regional anesthesia from clinical notes.
Regional anesthesia and pain medicine
Mar 5, 2025
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
Mar 3, 2025
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
Jan 28, 2025
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
Jan 22, 2025
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
Dec 4, 2024
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...
Identifying the Severity of Heart Valve Stenosis and Regurgitation Among a Diverse Population Within an Integrated Health Care System: Natural Language Processing Approach.
JMIR cardio
Sep 30, 2024
BACKGROUND: Valvular heart disease (VHD) is a leading cause of cardiovascular morbidity and mortality that poses a substantial health care and economic burden on health care systems. Administrative diagnostic codes for ascertaining VHD diagnosis are ...
Rule-based natural language processing to examine variation in worsening heart failure hospitalizations by age, sex, race and ethnicity, and left ventricular ejection fraction.
American heart journal
Sep 7, 2024
BACKGROUND: Prior studies characterizing worsening heart failure events (WHFE) have been limited in using structured healthcare data from hospitalizations, and with little exploration of sociodemographic variation. The current study examined the impa...
Predicting Short Time-to-Crime Guns: a Machine Learning Analysis of California Transaction Records (2010-2021).
Journal of urban health : bulletin of the New York Academy of Medicine
Sep 5, 2024
Gun-related crime continues to be an urgent public health and safety problem in cities across the US. A key question is: how are firearms diverted from the legal retail market into the hands of gun offenders? With close to 8 million legal firearm tra...
Deep learning models map rapid plant species changes from citizen science and remote sensing data.
Proceedings of the National Academy of Sciences of the United States of America
Sep 5, 2024
Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learni...
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