AIMC Topic: Hispanic or Latino

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Algorithmic Fairness of Machine Learning Models for Alzheimer Disease Progression.

JAMA network open
IMPORTANCE: Predictive models using machine learning techniques have potential to improve early detection and management of Alzheimer disease (AD). However, these models potentially have biases and may perpetuate or exacerbate existing disparities.

Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population.

Scientific reports
Reference intervals (RIs) for clinical laboratory values are extremely important for diagnostics and treatment of patients. However, the determination of these ranges is costly and time-consuming. As a result, often different unverified RIs are used ...

Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.

Journal of telemedicine and telecare
INTRODUCTION: Age-related macular degeneration, diabetic retinopathy, and glaucoma are vision-threatening diseases that are leading causes of vision loss. Many studies have validated deep learning artificial intelligence for image-based diagnosis of ...

Evaluation of AIML + HDR-A Course to Enhance Data Science Workforce Capacity for Hispanic Biomedical Researchers.

International journal of environmental research and public health
Artificial intelligence (AI) and machine learning (ML) facilitate the creation of revolutionary medical techniques. Unfortunately, biases in current AI and ML approaches are perpetuating minority health inequity. One of the strategies to solve this p...

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Unhealthy alcohol use represents a major economic burden and cause of morbidity and mortality in the United States. Implementation of interventions for unhealthy alcohol use depends on the availability and accuracy of screening tools. Our group previ...

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...

Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study.

The Lancet. Digital health
BACKGROUND: Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic screening services. We, therefore, aimed to develop and evaluate a machine learning-based screening te...

Reflections of Low-Income, Second-Generation Latinas About Experiences in Depression Therapy.

Qualitative health research
Depression is higher among second-generation Latinas compared with immigrants, but mental health treatment is stigmatized. Therefore, second-generation Latinas were interviewed after completing an eight-session depression treatment program to gain in...