Daniel Malinsky
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View article: Quantifying the impact of early life growth adversity on later life health
Quantifying the impact of early life growth adversity on later life health Open
Background Early-life growth adversity is important to later-life health, but precision assessment in adulthood is challenging. We evaluated whether the difference between attained and genotype-predicted adult height (“height-GaP”) would a…
View article: Mediation Analysis in the Presence of Sample Selection Bias with an Application to Disparities in Liver Transplantation Listing
Mediation Analysis in the Presence of Sample Selection Bias with an Application to Disparities in Liver Transplantation Listing Open
The study of disparities in the liver transplantation process may focus on quantifying causal effects, particularly the average, direct, or indirect effects of various social determinants of health on being listed as a candidate for transp…
View article: Bridging Prediction and Intervention Problems in Social Systems
Bridging Prediction and Intervention Problems in Social Systems Open
Many automated decision systems (ADS) are designed to solve prediction problems -- where the goal is to learn patterns from a sample of the population and apply them to individuals from the same population. In reality, these prediction sys…
View article: Intrinsic health as a foundation for a science of health
Intrinsic health as a foundation for a science of health Open
The health sciences largely focus on disease. However, the interconnected determinants of diseases suggest that we need a science of health, a framework to examine the biology of homeodynamics in a changing environment and how this affects…
View article: Quantifying the impact of early-life growth adversity on later-life health
Quantifying the impact of early-life growth adversity on later-life health Open
Background Early-life growth adversity is important to later-life health, but precision assessment in adulthood is challenging. We evaluated whether the difference between attained and genotype-predicted adult height (“height-GaP”) would a…
View article: Corrigendum to “Estimating bounds on causal effects in high-dimensional and possibly confounded systems” [Int. J. Approx. Reason. 88 (2017) 371–384]
Corrigendum to “Estimating bounds on causal effects in high-dimensional and possibly confounded systems” [Int. J. Approx. Reason. 88 (2017) 371–384] Open
View article: AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation
AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation Open
The primary practice of healthcare artificial intelligence (AI) starts with model development, often using state-of-the-art AI, retrospectively evaluated using metrics lifted from the AI literature like AUROC and DICE score. However, good …
View article: Mediated probabilities of causation
Mediated probabilities of causation Open
We propose a set of causal estimands that we call “the mediated probabilities of causation.” These estimands quantify the probabilities that an observed negative outcome was induced via a mediating pathway versus a direct pathway in a styl…
View article: Quantile Graph Discovery through QuACC: Quantile Association via Conditional Concordance
Quantile Graph Discovery through QuACC: Quantile Association via Conditional Concordance Open
Graphical structure learning is an effective way to assess and visualize cross-biomarker dependencies in biomedical settings. Standard approaches to estimating graphs rely on conditional independence tests that may not be sensitive to asso…
View article: Intrinsic Health as a Foundation for a Science of Health
Intrinsic Health as a Foundation for a Science of Health Open
The health sciences largely focus on disease. However, the interconnected determinants of diseases suggest that we need a Science of Health, a framework to examine the biology of homeodynamics in a changing environment and how this impacts…
View article: Post-selection inference for causal effects after causal discovery
Post-selection inference for causal effects after causal discovery Open
Algorithms for constraint-based causal discovery select graphical causal models among a space of possible candidates (e.g., all directed acyclic graphs) by executing a sequence of conditional independence tests. These may be used to inform…
View article: Longitudinal patterns of natural hazard exposures and anxiety and depression symptoms among young adults in four low- and middle-income countries
Longitudinal patterns of natural hazard exposures and anxiety and depression symptoms among young adults in four low- and middle-income countries Open
We estimated the effect of community-level natural hazard exposure during prior developmental stages on later anxiety and depression symptoms among young adults and potential differences stratified by gender. We analyzed longitudinal data …
View article: A cautious approach to constraint-based causal model selection
A cautious approach to constraint-based causal model selection Open
We study the data-driven selection of causal graphical models using constraint-based algorithms, which determine the existence or non-existence of edges (causal connections) in a graph based on testing a series of conditional independence …
View article: Mediated probabilities of causation
Mediated probabilities of causation Open
We propose a set of causal estimands that we call the "mediated probabilities of causation." These estimands quantify the probabilities that an observed negative outcome was induced via a mediating pathway versus a direct pathway in a styl…
View article: Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease
Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease Open
Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in p…
View article: UNDERSTANDING THE DYNAMICS OF INTRINSIC HEALTH USING AGE-DEPENDENT QUANTILE GRAPHICAL MODELS
UNDERSTANDING THE DYNAMICS OF INTRINSIC HEALTH USING AGE-DEPENDENT QUANTILE GRAPHICAL MODELS Open
Human health is a complex and dynamic system. Individual components, such as clinical biomarkers, vary jointly as an ensemble, and appropriate models are needed to study them in the context of health. Network analysis is an effective way t…
View article: QUANTIFYING INTRINSIC HEALTH USING STRESS-EVOKED INFORMATION FLOW BETWEEN PHYSIOLOGICAL SYSTEMS
QUANTIFYING INTRINSIC HEALTH USING STRESS-EVOKED INFORMATION FLOW BETWEEN PHYSIOLOGICAL SYSTEMS Open
As a canonical complex dynamical system, human bodies require interactions between constituent physiological systems to perform functions and maintain health status. Quantifying the dynamic interactions between organ systems using biomarke…
View article: The Effect of the Earned Income Tax Credit on Physical and Mental health—Results from the Atlanta Paycheck Plus Experiment
The Effect of the Earned Income Tax Credit on Physical and Mental health—Results from the Atlanta Paycheck Plus Experiment Open
Policy Points The Paycheck Plus randomized controlled trial tested a fourfold increase in the Earned Income Tax Credit (EITC) for single adults without dependent children over 3 years in New York and Atlanta. In New York, the intervention …
View article: Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study
Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study Open
Background: The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variabil…
View article: Causal Inference With Outcome-Dependent Missingness And Self-Censoring
Causal Inference With Outcome-Dependent Missingness And Self-Censoring Open
We consider missingness in the context of causal inference when the outcome of interest may be missing. If the outcome directly affects its own missingness status, i.e., it is "self-censoring", this may lead to severely biased causal effec…
View article: Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans
Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans Open
Background Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subt…
View article: Association of dysanapsis with mortality among older adults
Association of dysanapsis with mortality among older adults Open
Dysanapsis – an anthropometric mismatch between airway tree calibre and lung size that is common in the general population – is strongly associated with all-cause mortality and increases susceptibility to tobacco smoking-related diseases h…
View article: Critical interactions between race and the highly granular area deprivation index in liver transplant evaluation
Critical interactions between race and the highly granular area deprivation index in liver transplant evaluation Open
Neighborhood socioeconomic deprivation may have important implications on disparities in liver transplant (LT) evaluation. In this retrospective cohort study, we constructed a novel dataset by linking individual patient‐level data with the…
View article: Mapping Alveolar Oxygen Partial Pressure in COPD Using Hyperpolarized Helium-3: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study
Mapping Alveolar Oxygen Partial Pressure in COPD Using Hyperpolarized Helium-3: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study Open
Chronic obstructive pulmonary disease (COPD) and emphysema are characterized by functional and structural damage which increases the spaces for gaseous diffusion and impairs oxygen exchange. Here we explore the potential for hyperpolarized…
View article: Causal determinants of postoperative length of stay in cardiac surgery using causal graphical learning
Causal determinants of postoperative length of stay in cardiac surgery using causal graphical learning Open
View article: Multicenter study of racial and ethnic inequities in liver transplantation evaluation: Understanding mechanisms and identifying solutions
Multicenter study of racial and ethnic inequities in liver transplantation evaluation: Understanding mechanisms and identifying solutions Open
Racial and ethnic disparities persist in access to the liver transplantation (LT) waiting list; however, there is limited knowledge about underlying system‐level factors that may be responsible for these disparities. Given the complex natu…
View article: Disease-Specific Contribution of Pulvinar Dysfunction to Impaired Emotion Recognition in Schizophrenia
Disease-Specific Contribution of Pulvinar Dysfunction to Impaired Emotion Recognition in Schizophrenia Open
One important aspect for managing social interactions is the ability to perceive and respond to facial expressions rapidly and accurately. This ability is highly dependent upon intact processing within both cortical and subcortical compone…
View article: Disease-specific contribution of pulvinar dysfunction to impaired emotion recognition in schizophrenia
Disease-specific contribution of pulvinar dysfunction to impaired emotion recognition in schizophrenia Open
One important aspect for managing social interactions is the ability to rapidly and accurately perceive and respond to facial expressions, which is highly dependent upon intact processing within both cortical and subcortical components of …
View article: Differentiable Causal Discovery Under Unmeasured Confounding
Differentiable Causal Discovery Under Unmeasured Confounding Open
The data drawn from biological, economic, and social systems are often confounded due to the presence of unmeasured variables. Prior work in causal discovery has focused on discrete search procedures for selecting acyclic directed mixed gr…
View article: Semiparametric Inference for Nonmonotone Missing-Not-at-Random Data: The No Self-Censoring Model
Semiparametric Inference for Nonmonotone Missing-Not-at-Random Data: The No Self-Censoring Model Open
We study the identification and estimation of statistical functionals of multivariate data missing nonmonotonically and not-at-random, taking a semiparametric approach. Specifically, we assume that the missingness mechanism satisfies what …