Machine learning and clinical informatics for improving HIV care continuum outcomes
JP Ridgway, A Lee, S Devlin, J Kerman… - Current HIV/AIDS …, 2021 - Springer
Abstract Purpose of Review This manuscript reviews the use of electronic medical record
(EMR) data for HIV care and research along the HIV care continuum with a specific focus on …
(EMR) data for HIV care and research along the HIV care continuum with a specific focus on …
[HTML][HTML] Social and behavioral determinants of health in the era of artificial intelligence with electronic health records: a sco** review
KBS Agnikula, E Balls-BerryJoyce Joy - Health Data Science, 2021 - spj.science.org
Background. There is growing evidence that social and behavioral determinants of health
(SBDH) play a substantial effect in a wide range of health outcomes. Electronic health …
(SBDH) play a substantial effect in a wide range of health outcomes. Electronic health …
Predictive analytics in HIV surveillance require new approaches to data ethics, rights, and regulation in public health
In recent years, applications of big data-driven predictive analytics in public health programs
have expanded, offering promises of greater efficiency and improved outcomes. This …
have expanded, offering promises of greater efficiency and improved outcomes. This …
Studying patterns and predictors of HIV viral suppression using A Big Data approach: a research protocol
Background Given the importance of viral suppression in ending the HIV epidemic in the US
and elsewhere, an optimal predictive model of viral status can help clinicians identify those …
and elsewhere, an optimal predictive model of viral status can help clinicians identify those …
Utilizing electronic health record data to understand comorbidity burden among people living with HIV: a machine learning approach
Objectives: An understanding of the predictors of comorbidity among people living with HIV
(PLWH) is critical for effective HIV care management. In this study, we identified predictors of …
(PLWH) is critical for effective HIV care management. In this study, we identified predictors of …
Development of a predictive model for retention in HIV care using natural language processing of clinical notes
Objective Adherence to a treatment plan from HIV-positive patients is necessary to decrease
their mortality and improve their quality of life, however some patients display poor …
their mortality and improve their quality of life, however some patients display poor …
Comorbidity patterns among people living with HIV: a hierarchical clustering approach through integrated electronic health records data in South Carolina
Comorbidity among people living with HIV (PLWH) is understudied although identifying its
patterns and socio-demographic predictors would be beneficial for comorbidity …
patterns and socio-demographic predictors would be beneficial for comorbidity …
Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a …
Introduction The COVID-19 pandemic has affected communities of colour the hardest. Non-
Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV …
Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV …
Multicenter development and validation of a model for predicting retention in care among people with HIV
Predictive analytics can be used to identify people with HIV currently retained in care who
are at risk for future disengagement from care, allowing for prioritization of retention …
are at risk for future disengagement from care, allowing for prioritization of retention …
Emergence and evolution of big data science in HIV research: bibliometric analysis of federally sponsored studies 2000–2019
Background The rapid growth of inherently complex and heterogeneous data in HIV/AIDS
research underscores the importance of Big Data Science. Recently, there have been …
research underscores the importance of Big Data Science. Recently, there have been …