AIMC Topic: Texas

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Causal predictive modeling of survival of lung and bronchus cancer patients diagnosed during 2010-2011 in Texas.

PloS one
BACKGROUND: Lung and Bronchus cancer is the most fatal type of cancer in the United States. According to the American Cancer Society, there were more than 127,000 deaths from lung cancer in 2023. Lung cancer care cost 23.8 billion dollars in 2020. In...

The Alongside Digital Wellness Program for Youth: Longitudinal Pre-Post Outcomes Study.

JMIR formative research
BACKGROUND: Youth are increasingly experiencing psychological distress. Schools are ideal settings for disseminating mental health support, but they are often insufficiently resourced to do so. Digital mental health tools represent a unique avenue to...

Optimizing models for the prediction of one step ahead extreme flows to wastewater treatment plants using different synthetic sampling methods.

Journal of environmental management
High-flow events that significantly impact Water Resource Recovery Facility (WRRF) operations are rare, but accurately predicting these flows could improve treatment operations. Data-driven modeling approaches could be used; however, high flow events...

Children on wheels: Identifying crash determinants using cluster correspondence analysis.

Accident; analysis and prevention
Child bicyclists (14 years old and younger) are among the most vulnerable road users, facing significant risks of crashes that often result in severe injuries or fatalities. This study aims to identify key factors influencing child bicyclist crashes ...

Assessing Huanglongbing Severity and Canopy Parameters of the Huanglongbing-Affected Citrus in Texas Using Unmanned Aerial System-Based Remote Sensing and Machine Learning.

Sensors (Basel, Switzerland)
Huanglongbing (HLB), also known as citrus greening disease, is a devastating disease of citrus. However, there is no known cure so far. Recently, under Section 24(c) of the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA), a special local ...

Unmasking the sky: high-resolution PM prediction in Texas using machine learning techniques.

Journal of exposure science & environmental epidemiology
BACKGROUND: Although PM (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies.

Reconstruction of missing spring discharge by using deep learning models with ensemble empirical mode decomposition of precipitation.

Environmental science and pollution research international
A continuous and complete spring discharge record is critical in understanding the hydrodynamic behavior of karst aquifers and the variability of freshwater resources. However, due to equipment errors, failure of observation and other reasons, missin...

Integration of automated vehicles in mixed traffic: Evaluating changes in performance of following human-driven vehicles.

Accident; analysis and prevention
The introduction of Automated Vehicles (AVs) into the transportation network is expected to improve system performance, but the impacts of AVs in mixed traffic streams have not been clearly studied. As AV's market penetration increases, the interacti...

Crash narrative classification: Identifying agricultural crashes using machine learning with curated keywords.

Traffic injury prevention
OBJECTIVE: Traditionally, structured or coded data fields from a crash report are the basis for identifying crashes involving different types of vehicles, such as farm equipment. However, using only the structured data can lead to misclassification o...

Population demographics in geographic proximity to hospitals with robotic platforms do not correlate with disparities in access to robotic surgery.

Surgical endoscopy
BACKGROUND: Disparities in access to robotic surgery have been shown on the local, regional, and national level. This study aims to see if the location of hospitals with robotic platforms (HWR) correlates with population trends to explain the dispari...