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Imitation by Predicting Observations
[article]
2021
arXiv
pre-print
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Imitation learning enables agents to reuse and adapt the hard-won expertise of others, offering a solution to several key challenges in learning behavior. Although it is easy to observe behavior in the real-world, the underlying actions may not be accessible. We present a new method for imitation solely from observations that achieves comparable performance to experts on challenging continuous control tasks while also exhibiting robustness in the presence of observations unrelated to the task.
arXiv:2107.03851v1
fatcat:vfo2yknbuzatpcxrc4zus3ewiu
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... ur method, which we call FORM (for "Future Observation Reward Model") is derived from an inverse RL objective and imitates using a model of expert behavior learned by generative modelling of the expert's observations, without needing ground truth actions. We show that FORM performs comparably to a strong baseline IRL method (GAIL) on the DeepMind Control Suite benchmark, while outperforming GAIL in the presence of task-irrelevant features.
Semi-supervised Calibration of Risk with Noisy Event Times (SCORNET) Using Electronic Health Record Data
[article]
2021
bioRxiv
pre-print
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others, 2017; Liang and others, 2016; Zhao and others, 2014; Uno and others, 2018; Hassett and others, 2017; Chubak and others, 2012; Choi and others, 2015; Kaji and others, 2019; Ruan and others, 2019; Ahuja ...
leverages the features used in MAP as well as 121 additional manually-selected EHR features including counts of relevant medications, ICD codes, and concept unique identifiers (CUIs) in clinical notes (Ahuja ...
doi:10.1101/2021.01.08.425976
fatcat:7j7vkvbbfzaerp6o5wmjeyo5ri
SAMGEP: A Novel Method for Prediction of Phenotype Event Times Using the Electronic Health Record
[article]
2021
medRxiv
pre-print
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Objective: While there exist numerous methods to predict binary phenotypes using electronic health record (EHR) data, few exist for prediction of phenotype event times, or equivalently phenotype state progression. Estimating such quantities could enable more powerful use of EHR data for temporal analyses such as survival and disease progression. We propose Semi-supervised Adaptive Markov Gaussian Embedding Process (SAMGEP), a semi-supervised machine learning algorithm to predict phenotype event
doi:10.1101/2021.03.07.21253096
fatcat:ahl3si5y65fajjtkyw6rqtqa5a
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... times using EHR data. Methods: SAMGEP broadly consists of four steps: (i) assemble time-evolving EHR features predictive of the target phenotype event, (ii) optimize weights for combining raw features and feature embeddings into dense patient-timepoint embeddings, (iii) fit supervised and semi-supervised Markov Gaussian Process models to this embedding progression to predict marginal phenotype probabilities at each timepoint, and (iv) take a weighted average of these supervised and semi-supervised predictions. SAMGEP models latent phenotype states as a binary Markov process, conditional on which patient- timepoint embeddings are assumed to follow a Gaussian Process. Results: SAMGEP achieves significantly improved AUCs and F1 scores relative to common machine learning approaches in both simulations and a real-world task using EHR data to predict multiple sclerosis relapse. It is particularly adept at predicting a patient's longitudinal phenotype course, which can be used to estimate population-level cumulative probability and count process estimators. Reassuringly, it is robust to a variety of generative model parameters. Discussion: SAMGEP's event time predictions can be used to estimate accurate phenotype progression curves for use in downstream temporal analyses, such as a survival study for comparative effectiveness research.
sureLDA: A Multi-Disease Automated Phenotyping Method for the Electronic Health Record
[article]
2020
bioRxiv
pre-print
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Objective: A major bottleneck hindering utilization of electronic health record (EHR) data for translational research is the lack of precise phenotype labels. Chart review as well as rule-based and supervised phenotyping approaches require laborious expert input, hampering applicability to studies that require many phenotypes to be defined and labeled de novo. Though ICD codes are often used as surrogates for true labels in this setting, these sometimes suffer from poor specificity. We propose
doi:10.1101/2020.04.13.038968
fatcat:bgk56aafpbfyjfyvgkoy54gn4u
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... fully automated topic modeling algorithm to simultaneously annotate multiple phenotypes. Methods: sureLDA is a label-free multidimensional phenotyping method. It first uses the PheNorm algorithm to initialize probabilities based on two surrogate features for each target phenotype, and then leverages these probabilities to constrain the Latent Dirichlet Allocation (LDA) topic model to generate phenotype-specific topics. Finally, it combines phenotype-feature counts with surrogates via clustering ensemble to yield final phenotype probabilities. Results: sureLDA achieves reliably high accuracy and precision across a range of simulated and real-world phenotypes. Its performance is robust to phenotype prevalence and relative informativeness of surogate versus non-surrogate features. It also exhibits powerful feature selection properties. Discussion: sureLDA combines attractive properties of PheNorm and LDA to achieve high accuracy and precision robust to diverse phenotype characteristics. It offers particular improvement for phenotypes insufficiently captured by a few surrogate features. Moreover, sureLDAs feature selection ability enables it to handle high feature dimensions and produce interpretable computational phenotypes. Conclusion: sureLDA is well suited toward large-scale EHR phenotyping for highly multi-phenotype applications such as PheWAS.
Influence of Socioeconomic Status Trajectories on Innate Immune Responsiveness in Children
2012
PLoS ONE
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Objectives: Lower socioeconomic status (SES) is consistently associated with poor health, yet little is known about the biological mechanisms underlying this inequality. In children, we examined the impact of early-life SES trajectories on the intensity of global innate immune activation, recognizing that excessive activation can be a precursor to inflammation and chronic disease. Methods: Stimulated interleukin-6 production, a measure of immune responsiveness, was analyzed ex vivo for 267
doi:10.1371/journal.pone.0038669
pmid:22685596
pmcid:PMC3369855
fatcat:35xisvz2b5ab7icdz3cnrrifxe
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... ian schoolchildren from a 1995 birth cohort in Manitoba, Canada. Childhood SES trajectories were determined from parentreported housing data using a longitudinal latent-class modeling technique. Multivariate regression was conducted with adjustment for potential confounders. Results: SES was inversely associated with innate immune responsiveness (p = 0.003), with persistently low-SES children exhibiting responses more than twice as intense as their high-SES counterparts. Despite initially lower SES, responses from children experiencing increasing SES trajectories throughout childhood were indistinguishable from high-SES children. Low-SES effects were strongest among overweight children (p,0.01). Independent of SES trajectories, immune responsiveness was increased in First Nations children (p,0.05) and urban children with atopic asthma (p,0.01). Conclusions: These results implicate differential immune activation in the association between SES and clinical outcomes, and broadly imply that SES interventions during childhood could limit or reverse the damaging biological effects of exposure to poverty during the preschool years.
Diagnosis of feline acute intermittent porphyria presenting with erythrodontia requires molecular analyses
2013
The Veterinary Journal
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Erythrodontia is the hallmark of human congenital erythropoietic porphyria (CEP), but is also a major phenotypic feature of acute intermittent porphyria (AIP) in cats. In this study, detailed biochemical and molecular analyses were performed on two unrelated cats with autosomal dominant AIP that presented with erythrodontia, yellow-brown urine and mild changes in erythrocytes. The cats had elevated concentrations of urinary 5-aminolevulinic acid and porphobilinogen, and half normal erythrocytic
doi:10.1016/j.tvjl.2013.10.008
pmid:24239138
pmcid:PMC3963809
fatcat:eoold74a6bc27ehjlvdiijftl4
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... hydroxymethylbilane synthase (HMBS) activity. Two novel HMBS mutations were detected; one cat had a deletion (c.107_110delACAG) and one cat had a splicing alteration (c.826-1G>A), both leading to premature stop codons and truncated proteins (p.D36Vfs*6 and p.L276Efs*6, respectively). These studies highlight the importance of appropriate biochemical and molecular genetic analyses for the accurate diagnoses of porphyrias in cats and extend the molecular genetic heterogeneity of feline AIP. Thus, although erythrodontia is a classic sign of congenital erythropoietic porphyria in human beings, cats with erythrodontia may have acute intermittent porphyria, a hepatic porphyria. The porphyrias are inborn errors of metabolism resulting from deficient activities of specific enzymes in the heme biosynthetic pathway. Acute hepatic porphyrias in human beings include autosomal dominant acute intermittent porphyria (AIP), hereditary coproporphyria (HCP), variegate porphyria (VP) and autosomal recessive 5-aminolevulinate dehydratase deficient porphyria (ADP). In these conditions, plasma and urinary concentrations of the porphyrin precursors 5-aminolevulinic acid (ALA) and porphobilinogen (PBG) are markedly increased during sudden, life-threatening neurological attacks. In contrast, human
Leveraging electronic health records data to predict multiple sclerosis disease activity
2021
Annals of Clinical and Translational Neurology
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Ahuja et al. ...
doi:10.1002/acn3.51324
pmid:33626237
pmcid:PMC8045951
fatcat:x65ty5wepzb6nd3azihov5emr4
Adsorption separation of heavier isotope gases in subnanometer carbon pores
2021
Nature Communications
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AbstractIsotopes of heavier gases including carbon (13C/14C), nitrogen (13N), and oxygen (18O) are highly important because they can be substituted for naturally occurring atoms without significantly perturbing the biochemical properties of the radiolabelled parent molecules. These labelled molecules are employed in clinical radiopharmaceuticals, in studies of brain disease and as imaging probes for advanced medical imaging techniques such as positron-emission tomography (PET). Established
doi:10.1038/s41467-020-20744-6
pmid:33483513
fatcat:gletlyel4vaxjm7ame3mgg5tom
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... llation-based isotope gas separation methods have a separation factor (S) below 1.05 and incur very high operating costs due to high energy consumption and long processing times, highlighting the need for new separation technologies. Here, we show a rapid and highly selective adsorption-based separation of 18O2 from 16O2 with S above 60 using nanoporous adsorbents operating near the boiling point of methane (112 K), which is accessible through cryogenic liquefied-natural-gas technology. A collective-nuclear-quantum effect difference between the ordered 18O2 and 16O2 molecular assemblies confined in subnanometer pores can explain the observed equilibrium separation and is applicable to other isotopic gases.
Inferring multimodal latent topics from electronic health records
2020
Nature Communications
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Electronic health records (EHR) are rich heterogeneous collections of patient health information, whose broad adoption provides clinicians and researchers unprecedented opportunities for health informatics, disease-risk prediction, actionable clinical recommendations, and precision medicine. However, EHRs present several modeling challenges, including highly sparse data matrices, noisy irregular clinical notes, arbitrary biases in billing code assignment, diagnosis-driven lab tests, and
doi:10.1038/s41467-020-16378-3
pmid:32439869
fatcat:jhbngeavxnh5zjtm7h44jko4o4
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... neous data types. To address these challenges, we present MixEHR, a multi-view Bayesian topic model. We demonstrate MixEHR on MIMIC-III, Mayo Clinic Bipolar Disorder, and Quebec Congenital Heart Disease EHR datasets. Qualitatively, MixEHR disease topics reveal meaningful combinations of clinical features across heterogeneous data types. Quantitatively, we observe superior prediction accuracy of diagnostic codes and lab test imputations compared to the state-of-art methods. We leverage the inferred patient topic mixtures to classify target diseases and predict mortality of patients in critical conditions. In all comparison, MixEHR confers competitive performance and reveals meaningful disease-related topics.
Association of Interleukin 6 Receptor Variant With Cardiovascular Disease Effects of Interleukin 6 Receptor Blocking Therapy
2018
JAMA cardiology
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Cai, Ahuja, Gaziano, Cho, O'Donnell, Liao); Brigham and Women's Hospital, Boston, Massachusetts
Atherosclerosis of native arteries of the extremities with intermittent claudication log
10 P Value ...
doi:10.1001/jamacardio.2018.2287
pmid:30090940
pmcid:PMC6233652
fatcat:ykkx3xwg7beqhd7bog2n6cu2yq
Page 6695 of Mathematical Reviews Vol. , Issue 2004h
[page]
2004
Mathematical Reviews
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E. .. 62047 Ahmed, Zafar 82040 Ahn, Inkyung 35054 Ahn, Min-Ho ...... 41002 Ahuja, O. ...
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Page 1443 of Mathematical Reviews Vol. , Issue 2001B
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2001
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M. ... 47016,47056 Arlinskii, Yury See Arlinskii, Yu. M. Armanious, M. ...
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Akcoglu, Mustafa Akemann, Charles A. Akhmedoy, M. ...
Page 4605 of Mathematical Reviews Vol. , Issue 2002F
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G. 54006-54007 Ahuja, Ravindra K. ...
See Abramovich, Yuri A. Abramovich, Yuri A. ................ 47079 Abramsky, Samson RUNNER: cc vs Ktnnnscoveeeaddewimeek Absil, P.-A. ...
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