2022
DOI: 10.1007/s11481-021-10045-0
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Cognitive Phenotypes of HIV Defined Using a Novel Data-driven Approach

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Cited by 10 publications
(9 citation statements)
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“…We also used gradient-boosted multivariate regression (GBM) (40,41) to explore predictors of CD4/CD8 T-cell ratio trajectory cluster classification using the more diverse range of multidimensional information available in the RV254/SEARCH 010 biorepository (e.g., cytokine profiles, cognitive performance, mental health). GBM is a form of ensemble machine learning that yields similar classification accuracy to more computationally intensive methods such as Super Learner (42) while minimizing error due to overfitting (43)(44)(45)(46)(47)(48)(49). We used the Python-based program CatBoost (40,41) to build the GBM models.…”
Section: Discussionmentioning
confidence: 99%
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“…We also used gradient-boosted multivariate regression (GBM) (40,41) to explore predictors of CD4/CD8 T-cell ratio trajectory cluster classification using the more diverse range of multidimensional information available in the RV254/SEARCH 010 biorepository (e.g., cytokine profiles, cognitive performance, mental health). GBM is a form of ensemble machine learning that yields similar classification accuracy to more computationally intensive methods such as Super Learner (42) while minimizing error due to overfitting (43)(44)(45)(46)(47)(48)(49). We used the Python-based program CatBoost (40,41) to build the GBM models.…”
Section: Discussionmentioning
confidence: 99%
“…Highly correlated features (r > 0.65) were managed by selecting the feature with the highest mutual information criterion value. Consistent with prior work (44)(45)(46)(47), the number of features in the final algorithm was determined by model saturation, defined as the point at which inclusion of additional features resulted in <1 standard deviation gain in classification accuracy relative to the base model. For the current analysis, model saturation was achieved with 10 features.…”
Section: Discussionmentioning
confidence: 99%
“…First, there is the accurate identification and quantitation of medical co-morbidities particularly pre-morbid psychiatric conditions and illness-associated psychological distress 12 . Second, appropriate correction for normative demographic effects are imperative to accurately and specifically determine if cognitive deficits are present and to quantify their severity 13 . Many existing cognitive studies of COVID-19 that used objective testing 14 (Table S1) have not appropriately controlled for demographics, mental health, and comorbid medical conditions.…”
mentioning
confidence: 99%
“…Second, appropriate correction for normative demographic effects are imperative to accurately and specifically determine if cognitive deficits are present and to quantify their severity 13 . Many existing cognitive studies of COVID-19 that used objective testing 14 (Table S1) have not appropriately controlled for demographics, mental health, and comorbid medical conditions.…”
mentioning
confidence: 99%
“…Although HIV-associated neurocognitive disorder was a prominent, debilitating comorbidity in the early days of the HIV epidemic, approximately half of PWH today experience milder forms of neurocognitive impairment ( 4 ). It is also increasingly clear that there are synergistic, bidirectional associations of HIV neuropathogenesis with substance use ( 5 7 ), which has been consistently identified as a risk factor for difficulties with HIV disease management and onward HIV transmission ( 8 10 ). These enduring social, psychological, and neurobehavioral challenges underscore the continued need for this special issue examining the interaction of HIV with mental health.…”
mentioning
confidence: 99%