Vijay Mago

• Doctor of Philosophy
• Professor (Associate) at Lakehead University

Family physicians in Ontario provide most of the primary care to the healthcare system. However, given their broad scope of practice, they often provide additional services including emergency medicine, hospital medicine, and palliative care. Understanding the spectrum of services provided by family physicians across different regions is important...

Due to the competitive nature of the construction industry, the efficiency of requirement analysis is important in enhancing client satisfaction and a company’s reputation. For example, determining the optimal configuration of panels (generally called panelization) that form the structure of a building is one aspect of cost estimation. However, exi...

Background The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine learning in this process both significant and inevitable. This development raises numerous ethical concerns. This study explored the ethical use of AI and machine learn...

BACKGROUND In the event of cardiac arrest, providing immediate, high-quality cardiopulmonary resuscitation (CPR) and applying a defibrillator are crucial for patient care. High-quality CPR is defined by chest compressions at a rate of 100–120 per minute and a compression depth of 50–60 mm. However, during an emergency, monitoring the count and dept...

The use of Twitter by healthcare organizations is an effective means of disseminating medical information to the public. However, the content of tweets can be influenced by various factors, such as health emergencies and medical breakthroughs. In this study, we conducted a discourse analysis to better understand how public and private healthcare or...

BACKGROUND The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine learning in this process both significant and inevitable. This development raises numerous ethical concerns. This study explored the ethical use of AI and machine learn...

Introduction: The emergency department (ED) in rural communities is essential for providing care to patients with urgent medical issues and those unable to access primary care. Recent physician staffing shortages have put many EDs at risk of temporary closure. Our goal was to describe the demographics and practices of the rural physicians providin...

Overcrowding is a well-known problem in hospitals and emergency departments (ED) that can negatively impact patients and staff. This study aims to present a machine learning model to detect a patient’s need for a Computed Tomography (CT) exam in the emergency department at the earliest possible time. The data for this work was collected from ED at...

Background In most cases, the abstracts of articles in the medical domain are publicly available. Although these are accessible by everyone, they are hard to comprehend for a wider audience due to the complex medical vocabulary. Thus, simplifying these complex abstracts is essential to make medical research accessible to the general public. Object...

BACKGROUND One of the hallmarks of unregulated drug markets is their unpredictability and constant evolution with newly introduced substances. People who use drugs and the public health workforce are often unaware of the appearance of new drugs on the unregulated market and their type, safe dosage, and potential adverse effects. This increases risk...

BackgroundA hallmark of unregulated drug markets is their unpredictability and constant evolution with newly introduced substances. People who use drugs and the public health workforce are often unaware of the appearance of new drugs on the unregulated market and their type, safe dosage, and potential adverse effects. This increases risks to people...

This study assesses the online societal association of leaders and healthcare organizations from the top-10 COVID-19 resilient nations through public engagement, sentiment strength, and inclusivity and diversity strength. After analyzing 173,071 Tweets authored by the leaders and health organizations, our findings indicate that United Arab Emirate’...

Background Twitter is a popular social networking site where short messages or “tweets” of users have been used extensively for research purposes. However, not much research has been done in mining the medical professions, such as detecting the occupations of users from their biographical contents. Mining such professions can be used to build effic...

This article provides a comprehensive summary of how candidates running in the 2020 US Presidential Elections used Twitter to communicate with the public. More specifically, it aims to uncover elements linked to public engagement and internal cooperation (in terms of content and stance similarity among the candidates from the same political front,...

Research community has witnessed substantial growth in the detection of mental health issues and their associated reasons from analysis of social media. We introduce a new dataset for Causal Analysis of Mental health issues in Social media posts (CAMS). Our contributions for causal analysis are two-fold: causal interpretation and causal categorizat...

Background In a sudden cardiac arrest, starting CPR and applying an AED immediately are the two highest resuscitation priorities. Many existing mobile applications have been developed to assist users in locating a nearby AED. However, these applications do not provide indoor navigation to the AED location. The time required to locate an AED inside...

Student mobility or academic mobility involves students moving between institutions during their post-secondary education, and one of the challenging tasks in this process is to assess the transfer credits to be offered to the incoming student. In general, this process involves domain experts comparing the learning outcomes of the courses, to decid...

Usability studies are a crucial part of developing user-centered designs and they can be conducted using a variety of different methods. Unmoderated usability surveys are more efficient and cost-effective and lend themselves better to larger participant pools in comparison to moderated usability surveys. However, unmoderated usability surveys could...

When modelling epidemics, the outputs and techniques used may be hard for the general public to understand. This can cause fear mongering and confusion on how to interpret the predictions provided by these models. This article proposes a solution for such a model that was created by a Canadian institute for COVID-19 in their region; namely, the Nor...

Influencing and framing debates on Twitter provides power to shape public opinion. Bots have become essential tools of ‘computational propaganda’ on social media such as Twitter, often contributing to a large fraction of the tweets regarding political events such as elections. Although analyses have been conducted regarding the first impeachment of...

The advent of spam on social media platforms has lead to a number of problems not only for social media users but also for researchers mining social media data. While there has been substantial research on automated methods of spam detection on Twitter, research on the lexical content of spam on the platform is limited. A dataset of 301 million gen...

Real-time online data processing is quickly becoming an essential tool in the analysis of social media for political trends, advertising, public health awareness programs and policy making. Traditionally, processes associated with offline analysis are productive and efficient only when the data collection is a one-time process. Currently, cutting e...

When working with an agent-based system, it may be desirable to develop an algorithm that can predict future time periods for each individual. One such approach that works to accomplish this is the Markov decision process, which takes as its input available actions, unique agent reward functions, and a model of the overall environment. However, it...

Background: Social media platforms (SMPs) are frequently used by various pharmaceutical companies, public health agencies, and NGOs for communicating health concerns, new advancements, and potential outbreaks. While the benefits of using them as a tool have been extensively discussed, the online activity of various healthcare organizations on SMPs...

Automatic sarcasm detection is a growing field in computer science. Short text messages are increasingly used for communication, especially over social media platforms such as Twitter. Due to insufficient or missing context, unidentified sarcasm in these messages can invert the meaning of a statement, leading to confusion and communication failures...

In recent years, social media has become a ubiquitous and integral part of social discourse. Homophily is a fundamental topic in network science and can provide insights into the flow of information and behaviours within society. Homophily mainly refers to the tendency of similar-minded people to interact with one another in social groups than with...

In recent days, with increased population and traffic on roadways, vehicle collision is one of the leading causes of death worldwide. The automotive industry is motivated on developing techniques to use sensors and advancements in the field of computer vision to build collision detection and collision prevention systems to assist drivers. In this a...

Semantic textual similarity is one of the open research challenges in the field of Natural Language Processing. Extensive research has been carried out in this field and near-perfect results are achieved by recent transformer-based models in existing benchmark datasets like the STS dataset and the SICK dataset. In this paper, we study the sentences...

Emotion recognition in conversations is an important step in various virtual chatbots which require opinion-based feedback, like in social media threads, online support, and many more applications. Current emotion recognition in conversations models face issues like: (a) loss of contextual information in between two dialogues of a conversation, (b)...

With the approval of vaccines for the coronavirus disease by many countries worldwide, most developed nations have begun, and developing nations are gearing up for the vaccination process. This has created an urgent need to provide a solution to optimally distribute the available vaccines once they are received by the authorities. In this paper, we...

Machine learning is one of the essential and effective tools in analyzing highly complex medical data. With vast amounts of medical data being generated, there is an urgent need to effectively use this data to benefit the medical and health care sectors all across the world. This survey paper presents a systematic literature review for the investig...

Emotion recognition in conversations is an important step in various virtual chat bots which require opinion-based feedback, like in social media threads, online support and many more applications. Current Emotion recognition in conversations models face issues like (a) loss of contextual information in between two dialogues of a conversation, (b)...

Student mobility or academic mobility involves students moving between institutions during their post-secondary education, and one of the challenging tasks in this process is to assess the transfer credits to be offered to the incoming student. In general, this process involves domain experts comparing the learning outcomes of the courses, to decid...

With the approval of vaccines for the coronavirus disease by many countries worldwide, most developed nations have begun, and developing nations are gearing up for the vaccination process. This has created an urgent need to provide a solution to optimally distribute the available vaccines once they are received by the authorities. In this paper, we...

Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP). The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. To address this issue, various semantic similarity methods have...

Twitter is a prominent multilingual social networking site where users can post messages known as “tweets”. Twitter, like other social networking sites such as Facebook, allows users to categorize tweets by the use of “hashtags”. Communication on Twitter can be mapped in terms of hashtag graphs, where vertices correspond to hashtags, and edges corr...

Background When an Out-of-Hospital Cardiac Arrest (OHCA) incident is reported to emergency services, the 911 agent dispatches Emergency Medical Services to the location and activates responder network system (RNS), if the option is available. The RNS notifies all the registered users in the vicinity of the cardiac arrest patient by sending alerts t...

Background The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model will be developed for predicting positively referenced, drug-related tweets. From this, trends and correlations can be determined....

Social media platforms have become a common venue for sharing experiences and knowledge about health-related topics. This research focuses on examining social media-based communication patterns related to diabetes on the Twitter platform. Specifically, we apply an updated methodology to examine changes in the current use of hash-tags, trending hash...

Semantic textual similarity is one of the open research challenges in the field of Natural Language Processing. Extensive research has been carried out in this field and near-perfect results are achieved by recent transformed based models in existing benchmark datasets like STS dataset and SICK dataset. In this paper, we study the sentences in thes...

Twitter is a well-known microblogging social site where users express their views and opinions in real-time. As a result, tweets tend to contain valuable information. With the advancements of deep learning in the domain of natural language processing, extracting meaningful information from tweets has become a growing interest among natural language...

Background: COVID-19 has the potential to disproportionately affect the rural, remote, and Indigenous populations who typically have a worse health status and live in substandard housing, often with overcrowding. Our aim is to investigate the potential effect of COVID-19 on intensive care unit (ICU) resources and mortality in northwestern Ontario....

In an era of Big Data where bigger is considered better, there lies an inherent question that pertains to this ideology. To what extent does this big data contribute to improved/enhanced predictive models? Current research on this topic suggests that the commonplace theory of the bigger, the better, is inaccurate and the bigger, does not always ind...

In recent years, social media has become a ubiquitous and integral part of social networking. One of the major attentions made by social researchers is the tendency of like-minded people to interact with one another in social groups, a concept which is known as Homophily. The study of homophily can provide eminent insights into the flow of informat...

In recent years, machine learning has seen an increasing presencein a large variety of fields, especially in health care and bioinformatics.More specifically, the field where machine learning algorithms have found most applications is Genetic Algorithms.The objective of this paper is to conduct a survey of articles published from 2015 onwards that...

Text Simplification (TS) aims to reduce the linguistic complexity of content to make it easier to understand. Research in TS has been of keen interest, especially as approaches to TS have shifted from manual, hand-crafted rules to automated simplification. This survey seeks to provide a comprehensive overview of TS, including a brief description of...

Twitter has withstood the test of time as a successful social networking platform. In many circles globally, the majority of users choose Twitter when choosing a social media outlet for reliable scientific information and news. However, the Twitter application programming interface (API) limitations do not allow for low-cost data science options fo...

When it comes to any problem, their causes, and solutions, people often have very different perspectives. Agreeing on the same course of action can sometimes be difficult. A causal map is a way to capture different perspectives people have about any situation. In this paper, we study the use of conversational artificial intelligence to capture and...

It is estimated that over 235,000 Canadians experience homelessness at some point each year. With the emergence of smart cities, it would be beneficial to leverage the processing power of deep learning to assist in the planning and testing of different policies to address this issue. When examining a population of homeless individuals, one can view...

Estimating the semantic similarity between text data is one of the challenging and open research problems in the field of Natural Language Processing (NLP). The versatility of natural language makes it difficult to define rule-based methods for determining semantic similarity measures. In order to address this issue, various semantic similarity met...

The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of collected Twitter data, models were developed for classifying drug-related tweets. Using topic pertaining keywords, such as slang and methods of drug consumption, a set of tweets was...

When conducting data analysis in the twenty-first century, social media is crucial to the analysis due to the ability to provide information on a variety of topics such as health, food, feedback on products, and many others. Presently, users utilize social media to share their daily lifestyles. For example, travel locations, exercises, and food are...

The smart city is a concept of utilizing digital technologies to improve and enhance the lives of a city’s inhabitants. This concept has been the subject of increasing interest over the past few years. However, most studies address improving aspects of a city’s infrastructure, such as information security, privacy, communication networks, governmen...

As the popularity of the portable document format (PDF) file format increases, research that facilitates PDF text analysis or extraction is necessary. Heading detection is a crucial component of PDF‐based text classification processes. This research involves training a supervised learning model to detect headings by systematically testing and selec...

Nowadays, everyone is surrounded by a large volume of data which is generated from multiple sources. Every day 2.5 quintillion bytes of data are created worldwide. It is a very complicated task to manage and extract useful information from social media platforms. As people are more interested in seeking online health guidance, the medical textual d...

Twitter is a valuable source for learning about public opinion and political communication. Applying data mining to Twitter content (i.e., “Twitter mining”) offers a way to analyze large numbers of tweets to help us understand political associations the public makes. However, the use of incivility and sarcasm in political discourse may pose a chall...

Manual grading of essays by humans is time-consuming and likely to be susceptible to inconsistencies and inaccuracies. In recent years, an abundance of research has been done to automate essay evaluation processes, yet little has been done to take into consideration the syntax, semantic coherence and sentiments of the essay’s text together. Our pro...

Homelessness affects a diverse population, including disproportionate numbers of men, young adults who have gone through the youth protection system, Indigenous, and LGBTQ2S, among other subgroups. Currently, the process by which homeless are distributed among available emergency shelters and transitional housing is highly decentralized. The develo...

** THIS WAS ORIGINALLY SUBMITTED TO THE CCC WHITE PAPER FOR SOCIAL GOOD COMPETITION ** When looking at a population of homeless individuals, there are many different states they can be in; such as the street or shelter. Simulating the transitions of these individuals between states can be a challenging task when considering the various conditions t...

Complex problems often require coordinated actions from stakeholders. Agreeing on a course of action can be challenging as stakeholders have different views or ‘mental models’ of how a problem is shaped by many interacting causes. Participatory modeling allows to externalize mental models in forms such as causal maps. Participants can be guided by...

Models are predominantly developed using either quantitative data (e.g., for structured equation models) or qualitative data obtained through questionnaires designed by researchers (e.g., for fuzzy cognitive maps). The wide availability of social media data and advances in natural language processing raise the possibility of developing models from...

BACKGROUND The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. OBJECTIVE Through the analysis of a collected set of Twitter data, a model will be developed for predicting positively referenced, drug-related tweets. From this, trends and correlations can be...

The semantic analysis field has a crucial role to play in the research related to text analytics. Calculating the semantic similarity between sentences is a long-standing problem in the area of natural language processing and it differs significantly as the domain of operation differs. In this paper, we present a methodology that can be applied acr...

Within the field of post-secondary student mobility, the assessment, and evaluation of transfer credit is a labor-intensive human intelligence task that is subject to time limits and human bias. This paper introduces a semi-automated approach to assessing transfer credit and generating articulation agreements between post-secondary institutions usi...

Increasing use of Portable Document Format (PDF) files has promoted research in analysing its layout for text extraction purposes. In this paper, we propose an algorithm for extracting text from PDF documents while considering document layout. Using this algorithm, we extract learning outcomes from academic course outlines. This research is aimed a...

As the Portable Document Format (PDF) file format increases in popularity, research in analysing its structure for text extraction and analysis is necessary. Detecting headings can be a crucial component of classifying and extracting meaningful data. This research involves training a supervised learning model to detect headings with features carefu...

With the ever increasing availability of open, clinical health data, there exists a deficiency of platforms to take advantage of it [1]. The global prevalence of diabetes has risen from 4.7% in 1980 to 8.5% in 2014 and continues to rise, placing an increased demand on hospital resources [2]. The management of diabetic patients within hospital can b...

The course description provided by instructors is an essential piece of information as it defines what is expected from the instructor and what he/she is going to deliver during a particular course. One of the key components of a course description is the Learning Objectives section. The contents of this section are used by program managers who are...

The course description provided by instructors is an important piece of information as it defines what is expected from the instructor and what he/she is going to deliver during a particular course. One of the key components of a course description is the Learning Outcomes section. The contents of this section are used by program managers who are t...

Calculating the semantic similarity between sentences is a long dealt problem in the area of natural language processing. The semantic analysis field has a crucial role to play in the research related to the text analytics. The semantic similarity differs as the domain of operation differs. In this paper, we present a methodology which deals with t...

This research study proposes a new method for automatic design of Fuzzy Cognitive Maps (FCM) using ordinal data based on the efficient capabilities of mixed graphical models. The approach is able to model all variables on the proper domain of ordinal data by combining a new class of Mixed Graphical Models (MGMs) with a structure estimation approach...