AIMC Topic: California

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Prenatal exposure to criteria air pollution and traffic-related air toxics and risk of autism spectrum disorder: A population-based cohort study of California births (1990-2018).

Environment international
BACKGROUND: Autism spectrum disorder (ASD) prevalence has risen steadily in California (CA) over several decades, with environmental factors like air pollution (AP) increasingly implicated. This study investigates associations between prenatal exposu...

Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex.

Parasites & vectors
BACKGROUND: Mosquito-borne diseases, such as malaria, dengue, and Zika, continue to pose significant threats to global health, resulting in millions of cases and thousands of deaths each year. Notably, only older mosquitoes can transmit these disease...

Exploring the link between grandmaternal air pollution exposure and Grandchild's ASD risk: A multigenerational population-based study in California.

Environment international
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increasing prevalence. While genetics play a strong causal role, among environmental factors, air pollution (AP) exposure in pregnancy and infancy has been strongly endo...

Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians.

JAMA network open
IMPORTANCE: The increase of electronic health record (EHR) work negatively impacts clinician well-being. One potential solution is incorporating an ambient artificial intelligence (AI) documentation platform.

Results From a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence With Conditional Economic Incentives Among Young Adults With HIV.

Journal of acquired immune deficiency syndromes (1999)
BACKGROUND: Despite improvements in antiretroviral therapy (ART) availability, suboptimal adherence is common among youth with HIV (YWH) and can increase drug resistance and poor clinical outcomes. Our study examined an innovative mobile app-based in...

Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Electronic medical records (EMRs) and population-based cancer registries contain information on cancer outcomes and treatment, yet rarely capture information on the timing of metastatic cancer recurrence, which is essential to understand can...

Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

Journal of clinical gastroenterology
OBJECTIVES: The aim of this study was to test the ability of a commercially available natural language processing (NLP) tool to accurately extract examination quality-related and large polyp information from colonoscopy reports with varying report fo...

Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach.

Critical care medicine
OBJECTIVES: Identifying subgroups of ICU patients with similar clinical needs and trajectories may provide a framework for more efficient ICU care through the design of care platforms tailored around patients' shared needs. However, objective methods...