AIMC Topic: Texas

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Using machine learning to examine the relationship between asthma and absenteeism.

Environmental monitoring and assessment
In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating ...

Complementing the power of deep learning with statistical model fusion: Probabilistic forecasting of influenza in Dallas County, Texas, USA.

Epidemics
Influenza is one of the main causes of death, not only in the USA but worldwide. Its significant economic and public health impacts necessitate development of accurate and efficient algorithms for forecasting of any upcoming influenza outbreaks. Most...

Machine learning approaches for predicting high cost high need patient expenditures in health care.

Biomedical engineering online
BACKGROUND: This paper studies the temporal consistency of health care expenditures in a large state Medicaid program. Predictive machine learning models were used to forecast the expenditures, especially for the high-cost, high-need (HCHN) patients.

Ground Glass Lesions on Chest Imaging: Evaluation of Reported Incidence in Cancer Patients Using Natural Language Processing.

The Annals of thoracic surgery
BACKGROUND: Ground glass opacities (GGOs) on computed tomography (CT) have gained significant recent attention, with unclear incidence and epidemiologic patterns. Natural language processing (NLP) is a powerful computing tool that collects variables ...

Robot-assisted laparoscopic pyeloplasty in infants using 5-mm instruments.

Journal of pediatric urology
BACKGROUND: Utilization of the robotic approach to pyeloplasty continues to grow in the field of pediatric urology. Adoption in the infant population has perhaps been the slowest because of the limited operative domain and relatively large instrument...

Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance.

The Journal of infectious diseases
BACKGROUND: Invasive mold infections (IMI) can lead to severe morbidity and mortality, but routine public health surveillance is lacking. Although extensive evaluation is needed for clinical diagnosis, case classification prediction models may inform...

Identifying environmental drivers of Aedes aegypti and Aedes albopictus abundance in the Dallas-Fort Worth metroplex using Random Forest modeling.

Journal of medical entomology
Aedes aegypti and Aedes albopictus are 2 medically important vectors that have established populations globally. In the United States, Ae. aegypti populations declined post-Ae. albopictus introduction, though both species now can be readily found thr...

Building and Beta-Testing Be Well Buddy Chatbot, a Secure, Credible and Trustworthy AI Chatbot That Will Not Misinform, Hallucinate or Stigmatize Substance Use Disorder: Development and Usability Study.

JMIR human factors
BACKGROUND: Artificially intelligent (AI) chatbots that deploy natural language processing and machine learning are becoming more common in health care to facilitate patient education and outreach; however, generative chatbots such as ChatGPT face ch...

Towards a HPV Vaccine Knowledgebase for Patient Education Content.

Studies in health technology and informatics
Human papillomavirus is a widespread sexually transmitted infection that can be prevented with vaccination. However, HPV vaccination rates in the United States are disappointingly low. This paper will introduce a patient oriented web ontology intende...