A5041190314- Mobile Health and mHealth Applications
- Asthma and respiratory diseases
- Digital Mental Health Interventions
- Advanced Graph Neural Networks
- Data Quality and Management
- Semantic Web and Ontologies
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Biomedical Text Mining and Ontologies
- Complex Network Analysis Techniques
- Scientific Computing and Data Management
- Context-Aware Activity Recognition Systems
- IoT and Edge/Fog Computing
- Air Quality Monitoring and Forecasting
- Machine Learning in Healthcare
- Explainable Artificial Intelligence (XAI)
- Cardiovascular Disease and Adiposity
- Expert finding and Q&A systems
- AI-based Problem Solving and Planning
- Cognitive Computing and Networks
- Augmented Reality Applications
- Dietary Effects on Health
- Evolutionary Algorithms and Applications
- Sleep and related disorders
- Artificial Immune Systems Applications
- Wikis in Education and Collaboration
University of South Carolina
2021-2024
Wright State University
2014-2022
LNM Institute of Information Technology
2015-2016
Mittal hospital
2013
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performance, and epidemic spread. Today, these many more can be at global scale thanks digital footprints that we generate when browsing Web or using social media platforms. Unfortunately, scientists often struggle access data primarily because it is proprietary, even shared with privacy guarantees, either no representative...
The Internet of Things refers to network-enabled technologies, including mobile and wearable devices, which are capable sensing actuation as well interaction communication with other similar devices over the Internet. IoT is profoundly redefining way we create, consume, share information. Ordinary citizens increasingly use these technologies track their sleep, food intake, activity, vital signs, physiological statuses. This activity complemented by systems that continuously collect process...
The term metaverse was coined by author Neal Stephenson in 1992 his science fiction novel "Snow Crash."1 Metaverse is a conjunction of the Greek prefix "meta," which means beyond, and stem "verse," implies universe, hence meaning "beyond universe." It futuristic, hyperrealistic virtual world where humans will spend time performing their day-to-day activities, such as entertaining, socializing, playing, working, shopping. This requires that offers real-time representation physical with its...
Monitoring indoor air quality is critical because Americans spend 93 of their life indoors, and around 6.3 million children suffer from asthma. We want to passively unobtrusively monitor the asthma patient's environment detect presence two asthma-exacerbating activities: smoking cooking using Foobot sensor. propose a data-driven approach develop continuous monitoring-activity detection system aimed at understanding improving in management. In this study, we were successfully able high...
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, disease focused wellness and quality life focused, clinic centric anywhere patient is, clinician controlled empowered, being driven by limited data 360-degree, multimodal personal-public-population physical-cyber-social big driven. While ability create capture already here, upcoming innovations will be converting this into smart contextual personalized processing such that patients...
In the traditional asthma management protocol, a child meets with clinician infrequently, once in 3 to 6 months, and is assessed using Asthma Control Test questionnaire. This information inadequate for timely determination of control, compliance, precise diagnosis cause, assessing effectiveness treatment plan. The continuous monitoring improved tracking child's symptoms, activities, sleep, adherence can allow triggers reliable assessment medication compliance effectiveness. Digital...
Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and avoiding these Clinicians cannot continuously monitor their patients' environment plan, which poses significant challenge for management.In this study, pediatric patients were monitored using low-cost sensors collect asthma-relevant information. The objective of study was assess whether kHealth kit, contains sensors, identify personalized triggers provide actionable...
Humans use causality and hypothetical retrospection in their daily decision-making, planning, understanding of life events.1 The human mind, while retrospecting a given situation, think about questions such as "What was the cause situation?," would be effect my action?," have happened if I had taken another action instead?," or "Which led to this effect?" mind has an innate causality.15 It develops causal model world, which learns with fewer data points, makes inferences, contemplates...
According to a study done in 2014 by National Health Interview Survey around 6.3 million children United States suffer from asthma [1]. Asthma remains one of the leading reasons for pediatric admissions children's hospitals, and has prevalence rate approximately 10% it leads missed days school other societal costs. This occurs despite improved medications control symptoms. management is challenging as involves understanding causes avoiding triggers that are both multi- factorial...
Causal discovery is a process of discovering new causal relations from observational data. Traditional methods often suffer issues related to missing data To address these issues, this paper presents novel approach called CausalDisco that formulates as knowledge graph completion problem. More specifically, the task mapped link prediction. supports two types discovery: explanation and The have weights representing strength association between entities in graph. An evaluation uses benchmark...
Causal neurosymbolic AI (NeSyAI) combines the benefits of causality with NeSyAI. More specifically, it 1) enriches NeSyAI systems explicit representations causality, 2) integrates causal knowledge domain knowledge, and 3) enables use techniques for tasks. The representation yields insights that predictive models may fail to analyze from observational data. It can also assist people in decision-making scenarios where discerning cause an outcome is necessary choose among various interventions.
Causal networks are often incomplete with missing causal links. This is due to various issues, such as observation data. Recent approaches the issue of have used knowledge graph link prediction methods find In A causes B C, influence C influenced by which known a mediator. Existing using do not consider these mediated paper presents HyperCausalLP, an approach designed links within network help mediator The problem formulated hyper-relational completion. uses model trained on mediators....
The current method for predicting causal links in knowledge graphs uses weighted relations. For a given link between cause-effect entities, the presence of confounder affects prediction, which can lead to spurious and inaccurate results. We aim block these confounders using backdoor path adjustment. Backdoor paths are non-causal association flows that connect \textit{cause-entity} \textit{effect-entity} through other variables. Removing ensures more accurate prediction links. This paper...
Sleep disorders are common in children with asthma and have been implicated poor control. Smart wearables such as the Fitbit wristband allow monitoring patients sleep duration quality their natural surroundings. However, utility efficacy of using wearable devices to monitor pediatric has not established. Children, ages 5 yrs. 18 yrs., participating kHealth Asthma research study at Dayton Children’s Hospital were included. The kit includes an android tablet a mobile health application that...
In Swarm Intelligence, every single agent works in a group as system to solve problem. There is no centralized force governing the system. Each uses its own wisdom work and collaborate with fellow agents constitute swarm intelligence. Therefore, plays key role Without problem solving an impossible task domain of life. This combination Wisdom known WisSwarm (Wisdom Swarm).
Swarm Intelligence has emerged as an important technique among various computational techniques due to its effieciency and robustness of the solution. The authors have categorized different swarm intelligence based on agents population involved space-time variation get optimal solution a problem.