Bioinformatics Commons^™

Building Iot Based Applications For Smart Cities: How Can Ontology Catalogs Help?, Amelia Gyrard, Antoine Zimmermann, Amit P. Sheth

Kno.e.sis Publications

The Internet of Things (IoT) plays an ever-increasing role in enabling smart city applications. An ontology-based semantic approach can help improve interoperability between a variety of IoT-generated as well as complementary data needed to drive these applications. While multiple ontology catalogs exist, using them for IoT and smart city applications require significant amount of work. In this paper, we demonstrate how can ontology catalogs be more effectively used to design and develop smart city applications? We consider four ontology catalogs that are relevant for IoT and smart cities: 1) READY4SmartCities; 2) linked open vocabulary (LOV); 3) OpenSensingCity (OSC); and 4) …

Using Electronic Health Records To Characterize Prescription Patterns: Focus On Antidepressants In Nonpsychiatric Outpatient Settings, Joseph J. Deferio, Tomer T. Levin, Judith Cukor, Samprit Banerjee, Rozan Abdulrahman, Amit P. Sheth, Neel Mehta, Jyotishman Pathak

Kno.e.sis Publications

Objective

To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods

A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a New York City-based academic medical center. Structured “medication–diagnosis” pairs for antidepressants from 35 325 patients between January 2010 and December 2015 were compared to the latest drug product labels and evidence assessments. Results

Of 140 929 antidepressant prescriptions prescribed by primary care providers (PCPs) and nonpsychiatry specialists, 69% were characterized as “on-label/evidence-based uses.” Depression diagnoses were associated …

Poster: Privacy-Preserving Boosting With Random Linear Classifiers, Sagar Sharma, Keke Chen

Kno.e.sis Publications

We propose SecureBoost, a privacy-preserving predictive modeling framework, that allows service providers (SPs) to build powerful boosting models over encrypted or randomly masked user submit- ted data. SecureBoost uses random linear classifiers (RLCs) as the base classifiers. A Cryptographic Service Provider (CSP) manages keys and assists the SP’s processing to reduce the complexity of the protocol constructions. The SP learns only the base models (i.e., RLCs) and the CSP learns only the weights of the base models and a limited leakage function. This separated parameter holding avoids any party from abusing the final model or conducting model-based attacks. We evaluate …

Collaborative Heroism: An Empirical Investigation, Dana Klisanin

Heroism Science

Interactive technologies have come to define our culture, and as such, they influence and shape our modes of perception and behavior. This empirical investigation explored the public’s perception of the impact of the Internet on heroism via assessment of a sample population through a process of item generation, sampling, and principal component analysis. A robust 5-component structure emerged with consensus among participants including: 1) Collaboration expands heroic potential; 2) Internet technology expands heroic potential; 3) Heroes are motivated to protect and serve; 4) Heroes are responsive to injustice; 5) Concern for others is a required ingredient. The results extend research …

Creating Real-Time Dynamic Knowledge Graphs, Swati Padhee, Sarasi Lalithsena, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Augmented Personalized Health: Using Semantically Integrated Multimodal Data For Patient Empowered Health Management Strategies, Amit P. Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, R. Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Kno.e.sis Publications

Healthcare as we know it is in the process of going through a massive change from:

1. Episodic to continuous

2. Disease-focused to wellness and quality of life focused

3. Clinic-centric to anywhere a patient is

4. Clinician controlled to patient empowered

5. Being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven URL: https://mhealth.md2k.org/2018-tech-showcase-home

Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth

Kno.e.sis Publications

Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of privacy nightmare. In this paper, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system …

De-Identified Interviews For The Study: Data Challenges Of Biomedical Researchers In The Age Of Omics, Rolando Garcia-Milian, Denise Hersey, Milica Vukmirovic

Rolando Garcia-Milian

Knowledge-Enabled Personalized Dashboard For Asthma Management In Children, Vaikunth Sridharan, Revathy Venkataramanan, Dipesh Kadariya, Krishnaprasad Thirunarayan, Amit Sheth, Maninder Kalra

Kno.e.sis Publications

Introduction: Childhood Asthma is a significant public health concern worldwide. Effective management of childhood asthma requires close monitoring of disease triggers, medication compliance and symptom control. The recent growth of the Internet of Things (IoT) based devices has enabled continuous monitoring of patients. kHealth-Asthma is a knowledge-enabled semantic framework consisting of IoT enabled sensors to record patient symptoms, medication usage and their environment. For each patient, 29 diverse parameters with 1852 data points are collected daily. kHealthDash platform enables real-time visual analysis at an individual and cohort level over such high volume, high variety data.

Methods: The kHealth kit was …

Short Courses: Flexible Learning Opportunities In Informatics, Amy Olex, Aaron R. Wolen, Julie Arendt, Karen H. Gau, F. Gerard Moeller

VCU Libraries Faculty and Staff Presentations

In today’s fast-paced, data-driven world, researchers need to have a good foundation in informatics to store, organize, process, and analyze growing amounts of data. However, not all degree programs offer such training. Obtaining training in informatics on your own can be a daunting task for both new and established researchers who have little informatics experience. Providing educational opportunities appropriate for various skill levels and that mesh with a full-time schedule can remove barriers and foster a collaborative, informatics-savvy community that is better equipped to push science forward.

To enhance informatics education in bioinformatics, VCUs Wright Center for Clinical and Translational …

Iot-Enhanced Human Experience, Amit P. Sheth, Biplav Srivastava, Florian Michahelles

Kno.e.sis Publications

The two articles in this special section represent ongoing Internet of Things applications in the context of Europe trying to make solutions usable to people in daily times.

Metrics For Evaluating Quality Of Embeddings For Ontological Concepts, Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit P. Sheth

Kno.e.sis Publications

Although there is an emerging trend towards generating embeddings for primarily unstructured data and, recently, for structured data, no systematic suite for measuring the quality of embeddings has been proposed yet. This deficiency is further sensed with respect to embeddings generated for structured data because there are no concrete evaluation metrics measuring the quality of the encoded structure as well as semantic patterns in the embedding space. In this paper, we introduce a framework containing three distinct tasks concerned with the individual aspects of ontological concepts: (i) the categorization aspect, (ii) the hierarchical aspect, and (iii) the relational aspect. Then, …

"What's Ur Type?" Contextualized Classification Of User Types In Marijuana-Related Communications Using Compositional Multiview Embedding, Ugur Kursuncu, Manas Gaur, Usha Lokala, Anurag Illendula, Krishnaprasad Thirunarayan, Raminta Daniulaityte, Amit P. Sheth, Budak Arpinar

Kno.e.sis Publications

With 93% of pro-marijuana population in US favoring legalization of medical marijuana, high expectations of a greater return for Marijuana stocks, and public actively sharing information about medical, recreational and business aspects related to marijuana, it is no surprise that marijuana culture is thriving on Twitter. After the legalization of marijuana for recreational and medical purposes in 29 states, there has been a dramatic increase in the volume of drug-related communication on Twitter. Specifically, Twitter accounts have been established for promotional and informational purposes, some prominent among them being American Ganja, Medical Marijuana Exchange, and Cannabis Now. Identification and characterization …

Personalized Prediction Of Suicide Risk For Web-Based Intervention, Amanuel Alambo, Manas Gaur, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jeremiah Schumm, Jyotishman Pathak, Amit P. Sheth

Kno.e.sis Publications

Across the United States, suicide is the second leading cause of death for people aged between 15 and 34, and younger people are more prone to mental health problems, suicidal thoughts, and behaviors. For instance, 80% of patients with Borderline Personality Disorder have suicide-related behaviors, and between 4-9% of them commit suicide. Moreover, the social stigma associated with mental health issues and suicide deter patients from sharing their experiences directly with others. In such a situation, social media that provides a free and open forum for voluntary expression can provide insights into suicide ideation and self-destructive behavior.

Reddit is a …

Poster: Image Disguising For Privacy-Preserving Deep Learning, Sagar Sharma, Keke Chen

Kno.e.sis Publications

No abstract provided.

Feasibility Of Recording Sleep Quality And Sleep Duration Using Fitbit In Children With Asthma, Amit Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, Revathy Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Kno.e.sis Publications

Sleep disorders are common in children with asthma and are increasingly implicated in poor asthma control. Smart wearables such as the Fitbit wristband allow monitoring of users’ sleep duration and quality in their natural surroundings. However, the utility and efficacy of using such wearable devices to monitor sleep in pediatric patients with asthma have not been well-established. Thus, the objective of this study is to demonstrate the feasibility of recording sleep quality and sleep duration using Fitbit in children with asthma.

Khealth: A Personalized Healthcare Approach For Pediatric Asthma, Utkarshani Jaimini, Hong Y. Yip, Revathy Venkataramanan, Dipesh Kadariya, Vaikunth Sridharan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra, Amit Sheth

Kno.e.sis Publications

Can we assess the asthma control level, determine vulnerability, and medication compliance for a patient? Can we understand the causal relationship between the asthma symptom and possible factors responsible for it? Can we reduce the number of asthma attacks through continuous monitoring of the patient’s health condition?

“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth

Kno.e.sis Publications

Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of the child’s symptoms, activities, sleep, and treatment adherence can allow precise determination of asthma triggers and a reliable assessment of medication compliance and effectiveness. Digital phenotyping refers to moment-by-moment quantification of the individual-level human phenotype in situ using data from …

Personalized Health Knowledge Graph, Amelia Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, Amit Sheth

Kno.e.sis Publications

Our current health applications do not adequately take into account contextual and personalized knowledge about patients. In order to design “Personalized Coach for Healthcare” applications to manage chronic diseases, there is a need to create a Personalized Healthcare Knowledge Graph (PHKG) that takes into consideration a patient’s health condition (personalized knowledge) and enriches that with contextualized knowledge from environmental sensors and Web of Data (e.g., symptoms and treatments for diseases). To develop PHKG, aggregating knowledge from various heterogeneous sources such as the Internet of Things (IoT) devices, clinical notes, and Electronic Medical Records (EMRs) is necessary. In this paper, we …

Khealth Digital Personalized Healthcare Technology For Pediatric Asthma, Utkarshani Jaimini, Hong Y. Yip, Revathy Venkataramanan, Dipesh Kadariya, Vaikunth Sridharan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra, Amit Sheth

Kno.e.sis Publications

Episodic:Traditional Clinician Centric Healthcare

Questions to be answered:

1.Can we reduce the number of asthma attacks through continuous monitoring of the patient's health condition?

2.Can we predict the asthma attack based on the data collected from the patient?

3.Can we predict the asthma vulnerability score for a patient?

4.Can we predict the asthma severity level of a patient?

5.Can we understand the casual relationship between the asthma symptom and the possible factors responsible for it?

Clinical Information Extraction From Unstructured Free-Texts, Mingzhe Tao

Legacy Theses & Dissertations (2009 - 2024)

Information extraction (IE) is a fundamental component of natural language processing (NLP) that provides a deeper understanding of the texts. In the clinical domain, documents prepared by medical experts (e.g., discharge summaries, drug labels, medical history records) contain a significant amount of clinically-relevant information that is crucial to the overall well-being of patients. Unfortunately, in many cases, clinically-relevant information is presented in an unstructured format, predominantly consisting of free-texts, making it inaccessible to computerized methods. Automatic extraction of this information can improve accessibility. However, the presence of synonymous expressions, medical acronyms, misspellings, negated phrases, and ambiguous terminologies make automatic extraction …