Jonathan P. BonaUniversity of Arkansas for Medical Sciences | UAMS · Department Biomedical Informatics
Jonathan P. Bona
Doctor of Philosophy
About
61
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214
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Citations since 2017
Publications
Publications (61)
Almost 40% of US adults provide informal caregiving, yet research gaps remain around what burdens affect informal caregivers. This study uses a novel social media site, Reddit, to mine and better understand what online communities focus on as their caregiving burdens. These forums were accessed using an application programming interface, a machine...
Background/Objective
Informed consent forms (ICFs) and practices vary widely across institutions. This project expands on previous work at the University of Arkansas for Medical Sciences (UAMS) Center for Health Literacy to develop a plain language ICF template. Our interdisciplinary team of researchers, comprised of biomedical informaticists, heal...
Background:
Previous studies have explored psychosocial effects as possible triggers of opioid overdose (OOD). However, little is known about the temporal association between OOD and prescribed controlled substance (CS) acquisition.
Objective:
The objective of this study was to evaluate the temporal relationship between OOD and acquiring prescri...
The Cancer Imaging Archive (TICA) receives and manages an ever-increasing quantity of clinical (non-image) data containing valuable information about subjects in imaging collections. To harmonize and integrate these data, we have first cataloged the types of information occurring across public TCIA collections. We then produced mappings for these d...
Neuroimaging is among the most active research domains for the creation and management of open-access data repositories. Notably lacking from most data repositories are integrated capabilities for semantic representation. The Arkansas Imaging Enterprise System (ARIES) is a research data management system which features integrated capabilities to su...
Objectives:
To facilitate clinical and translational research, imaging and non-imaging clinical data from multiple disparate systems must be aggregated for analysis. Study participant records from various sources are linked together and to patient records when possible to address research questions while ensuring patient privacy. This paper presen...
Published in Medical Physics, Vol. 47, No. 11
Purpose:
The dataset contains annotations for lung nodules collected by the Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) stored as standard DICOM objects. The annotations accompany a collection of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers, and correspond to "nodules ≥ 3...
PURPOSE
Precision medicine requires an understanding of individual variability, which can only be acquired from large data collections such as those supported by the Cancer Imaging Archive (TCIA). We have undertaken a program to extend the types of data TCIA can support. This, in turn, will enable TCIA to play a key role in precision medicine resea...
Background:
The Drug Ontology (DrOn) is a modular, extensible ontology of drug products, their ingredients, and their biological activity created to enable comparative effectiveness and health services researchers to query National Drug Codes (NDCs) that represent products by ingredient, by molecular disposition, by therapeutic disposition, and by...
Objectives: There exists a communication gap between the biomedical informatics community on one side and the computer science/artificial intelligence community on the other side regarding the meaning of the terms “semantic integration" and “knowledge representation“. This gap leads to approaches that attempt to provide one-to-one mappings between...
This paper proposes and reports on the creation of a biomedical ontology use patterns repository. This work aims to facilitate the curation, sharing, discovery, and use, of information about how OBO and other biomedical ontologies are used by informatics researchers and other ontology users to transform biomedical instance data into realist semanti...
The Arkansas Image Enterprise System (ARIES) pilot project brings together data from three collaborating investigative teams in an effort to identify common pathways of neurodegeneration. These datasets include images and image- derived features, motor assessments, cognitive assessments, clinical rating scales, demographics, and clinical data. ARIE...
The Arkansas Image Enterprise System (ARIES) is an instantiation of the Platform for Imaging in Precision Medicine (PRISM). PRISM containerizes The Cancer Image Archive (TCIA) technology stack, streamlining its deployment, and incorporating new tools to organize and analyze data. Its adoption improves TCIA's ability to manage and analyze integrated...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
The Cancer Imaging Archive (TCIA) hosts over 11 million de-identified medical images of cancer for research reuse, organized around DICOM-format radiological “Collections” related by disease type, modality, or research focus. Supporting non-image data are often provided as spreadsheets or other files lacking a common representation scheme. We are c...
The Drug Ontology (DrOn) is a modular, extensible ontology of drug products, their ingredients, and biological activity based on RxNorm and ChEBI. As part of ongoing DrOn development, we have identified the need to explicitly represent National Drug Codes (NDCs) -- numeric codes that are issued by the US Food and Drug Administration (FDA) and are u...
The Cancer Imaging Archive (TCIA) hosts over 11 million de-identified medical images related to cancer for research reuse. These are organized around DICOM-format radiological collections that are grouped by disease type, modality, or research focus. Many collections also include diverse non-image datasets in a variety of formats without a common a...
The Drug Ontology (DrOn) is a modular, extensible ontology of drug products, their ingredients, and biological activity based on RxNorm and ChEBI. As part of ongoing DrOn development, we have identified the need to explicitly represent National Drug Codes (NDCs) -- numeric codes that are issued by the US Food and Drug Administration (FDA) and are u...
The Cancer Imaging Archive (TCIA) hosts over 11 million de-identified medical images related to cancer for research reuse. These are organized around DICOM-format radiological collections that are grouped by disease type, modality, or research focus. Many collections also include diverse non-image datasets in a variety of formats without a common a...
The fully specified name of a concept in SNOMED CT is formed by a term to which in the typical case is added a semantic tag. The latter is meant to disambiguate homonymous terms and to indicate in which major subhierarchy of SNOMED CT that concept fits. We have developed a method to determine whether a concept's tag correctly identifies its place i...
In the biomedical domain, there exist a number of common data models (CDM) that have experienced wide uptake. However, none of these has emerged as the common model. Recently, the demand for integrating and analyzing increasingly large data sets in clinical and translational research has led to numerous efforts to harmonize existing CDMs and integr...
This work examines the January 31, 2017 International Release of SNOMED CT to determine the extent to which semantic tag usage by concepts matches concept placement in the hierarchy.
The fully specified name of a concept in SNOMED CT is formed by a term to which in the typical case is added a semantic tag (ST). An ST is meant to disambiguate homonymous terms and indicate where that concept fits into SNOMED's massive concept hierarchy. We have developed a method to determine whether or not a concept's tag correctly identifies it...
We have implemented a proof of concept that uses select terms from the Consumer Health Vocabulary and the Human Disease Ontology to annotate and index articles about mental health from PsychCentral.com. This paper presents the approach used and preliminary results, which indicate that processing health-related documents with the use of biomedical o...
SNOMED CT's Release Format 2 (RF2) has been announced as an improvement over its predecessor, for instance because of its more consistent and almost formal approach towards describing changes in components over different versions, as well as changes in the structure of SNOMED CT itself. We explore two sorts of changes that are only partially formal...
The Protein Ontology (PRO; http://purl.obolibrary.org/obo/pr) formally defines and describes taxon-specific and taxon-neutral protein-related entities in three major areas: proteins related by evolution; proteins produced from a given gene; and protein-containing complexes. PRO thus serves as a tool for referencing protein entities at any level of...
SNOMED CT's Release Format 2 (RF2) has been announced as an improvement over its predecessor, for instance because of its more consistent and almost formal approach towards describing changes in components over different versions, as well as changes in the structure of SNOMED CT itself. We explore two sorts of changes that are only partially formal...
Our preliminary investigation of the use of finding site associations in a small section of the SNOMED hierarchy reveals an important gap that limits the usefulness of the relevant concepts for representing and reasoning about cancer staging and its relation to patients, parts of their bodies, their health, and so on. We have used the presence of a...
We present an analysis of SNOMED CT ‘bleeding’ concepts – those concepts with descriptions that include ‘hematoma’, ‘hemorrhage’, or ‘bleeding’; or that are descended from ‘Bleeding (finding)’ in the Is-a hierarchy; or that have Hematomas or Hemorrhages as their associated morphology – to assess how consistently they are used in the ontology.
Migrating data from electronic healthcare records (EHR) to data repositories for biomedical research provides an opportunity for the design of extract-transfer-load procedures that not only make the repository a faithful representation of what is stated in the EHR, but also of how what is stated in the EHR (may or may not) correspond to what in rea...
SNOMED CT is a very large biomedical terminology supported by a concept-based ontology. In recent years it has been distributed under the new release format 'RF2'. RF2 provides a more consistent and coherent mechanism for keeping track of changes over versions, even to the extent that – in theory at least – any release will contain enough informati...
Some terminologies and ontologies, such as SNOMED CT, allow for post–coordinated as well as pre-coordinated expressions. Post–coordinated expressions are, essentially, small segments of the terminology graphs. Compositional expressions add logical and linguistic relations to the standard technique of post-coordination. In indexing medical text, man...
Amongst the positive outcomes expected from the Internet of Things for
Health are longitudinal patient records that are more complete and less erroneous
by complementing manual data entry with automatic data feeds from sensors.
Unfortunately, devices are fallible too. Quality control procedures such as
inspection, testing and maintenance can preven...
For sure, an unpleasant odor of feet may be categorized as an unpleasant odor. Though foot fetishists (De Block and Adriaens 2013), podiatrists and manufacturers of washing machines might disagree (Question Everything 2015), most people would contend such odor to be classified as an offensive odor. No clinician would have qualms in classifying an u...
This paper presents a model for explicit representations of amino acid sites in the protein ontology. We handle sites that are the locations of post-translational modifications, focusing on histone proteins as our initial test case. The work explicitly represents both the entities involved (sites, residues, etc), and commonly used information about...
We discuss the applicability of using the OBI assay paradigm for representing patient questionnaires, neuropsychological tests, and neurological exams, as well to annotate data generated from these assessments. We conclude that the specification for OBI ’assay’ employs a broad enough notion of evaluation to allow for these uses. However, it would b...
Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We...
The MGLAIR cognitive agent architecture includes a general model of modality and support for concurrent multimodal perception and action. It provides afferent and efferent modalities as instantiable objects used in agent implementations. Each modality is defined by a set of properties that govern its use and its integration with reasoning and actin...
GLAIR (Grounded Layered Architecture with Integrated Reasoning) is a multilayered cognitive architecture for embodied agents operating in real, virtual, or simulated environments containing other agents. The highest layer of the GLAIR Architecture, the Knowledge Layer (KL), contains the beliefs of the agent, and is the layer in which conscious reas...
Electronic health record-keeping systems in the Referent Tracking paradigm use globally unique identifiers to make explicit reference to all relevant particular entities, and structure data by referring to universals and relations defined in external, commonly-used ontologies. SNePS is a general-purpose Knowledge Representation, Reasoning and Actin...
The deployment of virtual characters in intermedia performance drives divergent agendas of this research group. From the perspective of performance studies, we examine the effect of computer-based characters as actors and believe explorations of mediated agency can open up new forms of engagement for live productions. From the visualisation point o...
PyRovio is our Python implementation of the WowWee Rovio API. It allows direct control of a Rovio robot from Python programs. We have used PyRovio to implement Python-based actor-agents that participate in a live intermedia performance. We also use PyRovio as part of ongoing work in cognitive robotics to connect SNePS-based agent minds to their Rov...
SNePS is a logic-based Knowledge Representation, Reasoning, and Acting system. We have created extensions to SNePS that allow its use as an ontology reasoning system, combining (1) instance data stored in a Referent Tracking 1 system, (2) facts from domain ontologies such as FMA, and (3) rules from a domain-independent ontological theory. This pape...
We describe preliminary work on semantic alarms, a framework for context-sensitive clinical alerts. Semantic alarms are intended for deployment in a multi-parameter vital sign monitoring system. Requirements for device and data interoperability within this system are discussed. Extended examples are provided for sepsis and congestive heart failure...
I propose to develop and implement a multimodal, grounded, layered, cognitive architecture for embodied agents. The field of cognitive architectures aims to replicate the types of cognitive functionality present in the human mind. The ability to sense and act simultaneously in different modalities is a key feature of humans and other biological cog...
Projects
Projects (2)
The Arkansas Image Enterprise System (ARIES) is an instantiation of the Platform for Imaging in Precision Medicine (PRISM). PRISM containerizes The Cancer Image Archive (TCIA) technology stack, streamlining its deployment, and incorporating new tools to organize and analyze data. ARIES is both a testbed for PRISM and an institutional research data management resource. It demonstrates the capabilities of the PRISM infrastructure’s semantic representation approach by integrating diverse data relevant to research questions about neurodegenerative disease.
