Computer Sciences Commons^™

Assessing Real-Time Flow Experience In Human-Computer Interaction: An Electroencephalogram (Eeg) Study, Fiona Fui-Hoon Nah, Tejaswini Yelamanchili, Keng Siau, Langtao Chen

Research Collection School Of Computing and Information Systems

An optimal experience termed flow can be experienced by users who are deeply involved in human-computer interaction (HCI). The electroencephalogram (EEG) provides an innovative way to assess in real-time if users are approaching or experiencing the flow state in various applications of HCI. However, the current literature remains unclear and inconsistent with regard to the relationship between EEG activity and flow experience. The objective of this research is to assess EEG activity corresponding to the state of flow. A laboratory experiment was conducted to collect EEG data of the flow and other states (including baseline) in the context of HCI.

Detecting Receptivity For Mhealth Interventions In The Natural Environment, Varun Mishra, Florian Künzler, Jan-Niklas Kramer, Elgar Fleisch, Tobias Kowatsch, David Kotz

Dartmouth Scholarship

Just-In-Time Adaptive Intervention (JITAI) is an emerging technique with great potential to support health behavior by providing the right type and amount of support at the right time. A crucial aspect of JITAIs is properly timing the delivery of interventions, to ensure that a user is receptive and ready to process and use the support provided. Some prior works have explored the association of context and some user-specific traits on receptivity, and have built post-study machine-learning models to detect receptivity. For effective intervention delivery, however, a JITAI system needs to make in-the-moment decisions about a user's receptivity. To this end, …

Computational Analysis Of Protein Stability And Allosteric Interaction Networks In Distinct Conformational Forms Of The Sars Cov 2 Spike D614g Mutant: Reconciling Functional Mechanisms Through Allosteric Model Of Spike Regulation, Gennady M. Verkhivker, Steve Agajanian, Deniz Oztas, Grace Gupta

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike …

Knowledge And Anxiety About Covid-19 In The State Of Qatar, And The Middle East And North Africa Region—A Cross Sectional Study, Sathyanarayanan Doraiswamy, Sohaila Cheema, Maisonneuve Patrick, Amit Abraham, Ingmar Weber, Jisun An, Albert B. Lowenfels, Ravinder Mamtani

Research Collection School Of Computing and Information Systems

While the coronavirus disease 2019 (COVID-19) pandemic wreaked havoc across the globe, we have witnessed substantial mis- and disinformation regarding various aspects of the disease. We conducted a cross-sectional study using a self-administered questionnaire for the general public (recruited via social media) and healthcare workers (recruited via email) from the State of Qatar, and the Middle East and North Africa region to understand the knowledge of and anxiety levels around COVID-19 (April–June 2020) during the early stage of the pandemic. The final dataset used for the analysis comprised of 1658 questionnaires (53.0% of 3129 received questionnaires; 1337 [80.6%] from the …

Modeling The Spread Of Covid-19 Over Varied Contact Networks, Ryan L. Solorzano

Master's Theses

When attempting to mitigate the spread of an epidemic without the use of a vaccine, many measures may be made to dampen the spread of the disease such as physically distancing and wearing masks. The implementation of an effective test and quarantine strategy on a population has the potential to make a large impact on the spread of the disease as well. Testing and quarantining strategies become difficult when a portion of the population are asymptomatic spreaders of the disease. Additionally, a study has shown that randomly testing a portion of a population for asymptomatic individuals makes a small impact …

Gaming Disorder And Well-Being Among Emirati College Women, Marina Verlinden, Justin Thomas, Mahra Hasan Abdulla Ahamed Almansoori, Shamil Wanigaratne

All Works

Background: The present study examined Internet Gaming Disorder (IGD) and depressive symptom levels among a predominantly female sample of college students from the United Arab Emirates (UAE). Methods: IGD was assessed among two successive cohorts of students at the beginning of the academic year in 2016 and 2019, respectively. All participants (n = 412) completed the Internet Gaming Disorder Scale – Short-Form (IGDS9-SF) and the WHO-5 Well-being Index (WHO-5), a tool widely used for the screening and assessment of depressive symptomatology. Results: Mean IGDS9-SF scores (15.85, SD = 6.40) were fairly similar to those observed in other nations. The prevalence …

Knowing What We Know: Leveraging Community Knowledge Through Automated Text-Mining, Justin Gardner, Jonathan Tory Toole, Hemant Kalia, Garry Spink Jr., Gordon Broderick

Advances in Clinical Medical Research and Healthcare Delivery

No abstract provided.

Deep Learning Predicts Chromosomal Instability From Histopathology Images, Zhuoran Xu, Akanksha Verma, Uska Naveed, Samuel F. Bakhoum, Pegah Khosravi, Olivier Elemento

Publications and Research

Chromosomal instability (CIN) is a hallmark of human cancer yet not readily testable for patients with cancer in routine clinical setting. In this study, we sought to explore whether CIN status can be predicted using ubiquitously available hematoxylin and eosin histology through a deep learning-based model. When applied to a cohort of 1,010 patients with breast cancer (Training set: n = 858, Test set: n = 152) from The Cancer Genome Atlas where 485 patients have high CIN status, our model accurately classified CIN status, achieving an area under the curve of 0.822 with 81.2% sensitivity and 68.7% specificity in …

Research Focus: Pattern Recognition

In The Loop

A CDM health informatics team joins a global race to advance COVID-19 diagnostics through X-ray insights.

An Analysis Of The Applications Of Technology To Health Care Within The Caribbean And Latin America, Chineme Ezema

School of Professional Studies

This project aims to investigate and document the evolution of health technology applications and uses within the regions of Latin America and the Caribbean. Originally inspired by the Cayman Islands’ thus far successful handling of the Coronavirus pandemic, I was eager to explore how the applications of technology to the field of healthcare have existed within the region currently and over time. With this foundation, I then explored the regions’ trajectory in terms of technological growth and what the future may hold for these countries and communities.

Title Ix: Perceptions And Utilization On U.S. College Campuses, Emma Narkewicz

School of Professional Studies

The research study investigated student perceptions and utilization of Title IX services on U.S. university and college campuses, testing the hypothesis that if students hold negative perceptions of Title IX offices, then they will not report campus sexual violence they experience to Title IX offices. There are currently high rates of sexual violence on college campuses but very low rates of reporting. Current or former U.S. college students aged 18-30 (N = 47) completed a mixed methods anonymous survey composed of Likert scale and open response questions. Participants were asked about prior interactions with Title IX offices and their perceptions …

Happening In Plain Sight: An Evaluation Of Sexual Harassment In Municipal Government Through A Case Study Of Newark, New Jersey, Hoween R. A. Flexer, Caitlin R. Louie

School of Professional Studies

In the city of Newark, New Jersey, Sebrevious Scott, a participant in the New Jersey Reentry program was hired as part-time office assistant in the city's re-entry office. After being transferred to the city’s Parks and Grounds Departments, she started being sexually harassed, inappropriately touched and propositioned by her supervisor, Richard Kirkland. Scott made repeated attempts to report these actions through the appropriate channels. She was met with dismissal, resistance, and later retaliation. While working in this hostile environment she was also pursuing a full-time employment opportunity with the city upon the completion of the reentry program. Unfortunately, this never …

Using Deep Learning To Analyze Materials In Medical Images, Carson Molder

Computer Science and Computer Engineering Undergraduate Honors Theses

Modern deep learning architectures have become increasingly popular in medicine, especially for analyzing medical images. In some medical applications, deep learning image analysis models have been more accurate at predicting medical conditions than experts. Deep learning has also been effective for material analysis on photographs. We aim to leverage deep learning to perform material analysis on medical images. Because material datasets for medicine are scarce, we first introduce a texture dataset generation algorithm that automatically samples desired textures from annotated or unannotated medical images. Second, we use a novel Siamese neural network called D-CNN to predict patch similarity and build …

Immigrant Families' Health-Related Information Behavior On Instant Messaging Platforms: Health-Related Information Exchange In Immigrant Family Groups On Instant Messaging Platforms, Lev Poretski, Taamannae Taabassum, Anthony Tang

Research Collection School Of Computing and Information Systems

For immigrant families, instant messaging family groups are a common platform for sharing and discussing health-related information. Immigrants often maintain contact with their family abroad and trust information in shared IM family groups more than the information from local authorities and sources. In this study, we aimed to understand health-related information behaviors of immigrant families in their IM family groups. Based on the interviews with 6 participants from immigrant families to Canada, we found that immigrant families’ discourse on IM platforms is motivated by love and care for other family members. The families used local and international sources of information, …

Using Deep Learning To Automate The Diagnosis Of Skin Melanoma, Akhil Reddy Alasandagutti

Honors Theses

Machine learning and image processing techniques have been widely implemented in the field of medicine to help accurately diagnose a multitude of medical conditions. The automated diagnosis of skin melanoma is one such instance. However, a majority of the successful machine learning models that have been implemented in the past have used deep learning approaches where only raw image data has been utilized to train machine learning models, such as neural networks. While they have been quite effective at predicting the condition of these lesions, they lack key information about the images, such as clinical data, and features that medical …

Improving Treatment Of Local Liver Ablation Therapy With Deep Learning And Biomechanical Modeling, Brian Anderson, Kristy Brock, Laurence Court, Carlos Eduardo Cardenas, Erik Cressman, Ankit Patel

Dissertations and Theses (Open Access)

In the United States, colorectal cancer is the third most diagnosed cancer, and 60-70% of patients will develop liver metastasis. While surgical liver resection of metastasis is the standard of care for treatment with curative intent, it is only avai lable to about 20% of patients. For patients who are not surgical candidates, local percutaneous ablation therapy (PTA) has been shown to have a similar 5-year overall survival rate. However, PTA can be a challenging procedure, largely due to spatial uncertainties in the localization of the ablation probe, and in measuring the delivered ablation margin.

For this work, we hypothesized …

A Comprehensive Review Of Retinal Vascular And Optical Nerve Diseases Based On Optical Coherence Tomography Angiography, Fatma Taher, Heba Kandil, Hatem Mahmoud, Ali Mahmoud, Ahmed Shalaby, Mohammed Ghazal, Marah Talal Alhalabi, Harpal Singh Sandhu, Ayman El-Baz

All Works

The optical coherence tomography angiography (OCTA) is a noninvasive imaging technology which aims at imaging blood vessels in retina by studying decorrelation signals between multiple sequential OCT B-scans captured in the same cross section. Obtaining various vascular plexuses including deep and superficial choriocapillaris, is possible, which helps in understanding the ischemic processes that affect different retina layers. OCTA is a safe imaging modality that does not use dye. OCTA is also fast as it can capture high-resolution images in just seconds. Additionally, it is used in the assessment of structure and blood flow. OCTA provides anatomic details in addition to …

A Novel Mra-Based Framework For Segmenting The Cerebrovascular System And Correlating Cerebral Vascular Changes To Mean Arterial Pressure, Fatma Taher, Heba Kandil, Yitzhak Gebru, Ali Mahmoud, Ahmed Shalaby, Shady El‐Mashad, Ayman El‐Baz

All Works

Blood pressure (BP) changes with age are widespread, and systemic high blood pressure (HBP) is a serious factor in developing strokes and cognitive impairment. A non‐invasive methodology to detect changes in human brain’s vasculature using Magnetic Resonance Angiography (MRA) data and correlation of cerebrovascular changes to mean arterial pressure (MAP) is pre-sented. MRA data and systemic blood pressure measurements were gathered from patients (n = 15, M = 8, F = 7, Age = 49.2 ± 7.3 years) over 700 days (an initial visit and then a follow‐up period of 2 years with a final visit.). A novel segmentation algorithm …

Oidpr: Optimized Insulin Dosage Via Privacy‐Preserving Reinforcement Learning, Zuobin Ying, Yun Zhang, Shuanglong Cao, Shengmin Xu, Maode Ma

Research Collection School Of Computing and Information Systems

The precision of insulin dosage is essential in the process of diabetes treatment. The fact is providing precise dosage is almost impossible for clinicians since blood sugar levels are dynamically affected by many factors. Even though some auxiliary dosing systems have been proposed, the required real‐time physical data about the health situation of diabetics is still hard to synchronize to the end‐devices instantly. The traditional personalized drug delivery frameworks for accurate dosing of insulin always collect and transmit medical data in cleartext, which raises privacy problems. In this article, we propose a framework for an optimized insulin dosage via privacy‐preserving …

The Effects Of Differences In Vaccination Rates Across Socioeconomic Groups On The Size Of Measles Outbreaks, Elizabeth Hunter, John D. Kelleher

Conference papers

Vaccination rates are often presented at the level of a country or region. However, within those areas there might be geographic or demographic pockets that have higher or lower vaccination rates. We use an agent-based model designed to simulate the spread of measles in Irish towns to examine if the effectiveness of vaccination rates to reduce disease at a population level is sensitive to the uniformity of vaccinations across socioeconomic groups. We find that when vaccinations are not applied evenly across socioeconomic groups we see more outbreaks and outbreaks with larger magnitudes.

App Development For Wearable Sensors, Connor Pittman, Christopher Chappie, Patrick A. Tetreault

Thinking Matters Symposium

The objective of this research project was to create a wearable device that monitors bodily functions for the user to view on their smartphone. Sensor data is processed using the Arduino Nano 33 BLE microcontroller. The sensors used in this project include: proximity, temperature, humidity, heart rate, pressure, and skin impedance. This project takes advantage of the Arduino's Bluetooth low energy (BLE) capabilities so that all the data can be transmitted to a smartphone. This presentation shows the challenges faced during the project and how they were overcome. Some of these challenges include: programming, how heart rate sensors work, and …

Implications Of The Quantum Dna Model For Information Sciences, F. Matthew Mihelic

Faculty Publications

The DNA molecule can be modeled as a quantum logic processor, and this model has been supported by pilot research that experimentally demonstrated non-local communication between cells in separated cell cultures. This modeling and pilot research have important implications for information sciences, providing a potential architecture for quantum computing that operates at room temperature and is scalable to millions of qubits, and including the potential for an entanglement communication system based upon the quantum DNA architecture. Such a system could be used to provide non-local quantum key distribution that could not be blocked by any shielding or water depth, would …

The Present And Future Of Artificial Intelligence In Ophthalmology, Robert Abishek, Elliot Cherkas

inSIGHT

Dr. Ravi Goel is a comprehensive ophthalmologist and cataract surgeon at Wills Eye Hospital, with a specific interest in finding ways that AI can help ophthalmologists improve their clinical care and treat more patients. Dr. Goel also publishes a daily blog, Protecting Sight, where he discusses a variety of topics ranging from advances in cataract surgery to medical education. One common thread throughout his blog is the burgeoning impact of AI on the field of ophthalmology, such as the utility of deep learning algorithms for diagnosing various diseases and the impact that improved intra-ocular lens (IOL) power calculations will have …

Combine Cryo-Em Density Map And Residue Contact For Protein Structure Prediction: A Case Study, Maytha Alshammari, Jing He

College of Sciences Posters

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments in 1D and a set of traces of secondary structures in 3D. In order to enhance the accuracy in ranking secondary structure topologies, we propose a method that combines three sources of information …

Ai Use In Claims Processing And Utilization Review, Robert Rosenthal Dds

The Journal of the Michigan Dental Association

This paper investigates the use of artificial intelligence (AI) in claims processing and utilization review in the dental industry. This article aims to explore the potential benefits of AI in this area, such as increased efficiency, accuracy, and fraud detection. The paper begins by providing an overview of the current state of claims processing and utilization review in the dental industry. It then discusses the potential applications of AI in this area, such as automated claims adjudication, predictive analytics, and image recognition. The paper then presents a case study of P&R Dental Strategies, LLC, a leading business intelligence solutions provider …

The Emergence Of Artificial Intelligence In Dental Care Delivery, Robert A. Faiella D.M.D., M.M.Sc., M.B.A., Shaju Puthussery M.S.

The Journal of the Michigan Dental Association

This comprehensive review explores the transformative role of Artificial Intelligence (AI) in the evolution of dental care delivery. As oral health specialists, dentists continually seek to enhance their ability to prevent, diagnose, and manage oral diseases while maintaining and improving patient oral health. The integration of AI offers unprecedented opportunities to revolutionize dental practice and patient care.

AI is rapidly advancing in healthcare, including dental care, with a projected global healthcare AI market value of $45.2 billion by 2026. This technology can potentially revolutionize prevention, diagnosis, treatment planning, and treatment outcomes.

Aspects of AI in dentistry include:

· Diagnostic Accuracy …

An Analysis Of The Interpretability Of Neural Networks Trained On Magnetic Resonance Imaging For Stroke Outcome Prediction, Esra Zihni, John D. Kelleher, Bryony Mcgarry

Conference papers

Applying deep learning models to MRI scans of acute stroke patients to extract features that are indicative of short-term outcome could assist a clinician’s treatment decisions. Deep learning models are usually accurate but are not easily interpretable. Here, we trained a convolutional neural network on ADC maps from hyperacute ischaemic stroke patients for prediction of short-term functional outcome and used an interpretability technique to highlight regions in the ADC maps that were most important in the prediction of a bad outcome. Although highly accurate, the model’s predictions were not based on aspects of the ADC maps related to stroke pathophysiology.

Bibliometric Analysis Of Named Entity Recognition For Chemoinformatics And Biomedical Information Extraction Of Ovarian Cancer, Vijayshri Khedkar, Charlotte Fernandes, Devshi Desai, Mansi R, Gurunath Chavan Dr, Sonali Tidke Dr., M. Karthikeyan Dr.

Library Philosophy and Practice (e-journal)

With the massive amount of data that has been generated in the form of unstructured text documents, Biomedical Named Entity Recognition (BioNER) is becoming increasingly important in the field of biomedical research. Since currently there does not exist any automatic archiving of the obtained results, a lot of this information remains hidden in the textual details and is not easily accessible for further analysis. Hence, text mining methods and natural language processing techniques are used for the extraction of information from such publications.Named entity recognition, is a subtask that comes under information extraction that focuses on finding and categorizing specific …

J Mich Dent Assoc April 2021

The Journal of the Michigan Dental Association

In the April 2021 issue of the Journal of the Michigan Dental Association, we offer a comprehensive range of original feature content showcasing the latest developments in dental practice and knowledge, including:

1. AI in Dental Care Delivery: Explore the groundbreaking role of Artificial Intelligence (AI) and Machine Learning in dental care, revolutionizing efficiency, safety, care outcomes, and treatment planning consistency.
2. AI in Dental Claims Processing: Discover how AI is employed by third-party payers to streamline dental claims processing, resulting in cost containment and the proactive identification of potential fraud, waste, and abuse.
3. Evidence-Based Dentistry: As part of …

10-Minute Ebd: Artificial Intelligence In Orthodontics, Jayne Kessel Dds

The Journal of the Michigan Dental Association

This Ten-Minute Evidence-Based Dentistry Article provides an example of the implementation of the EBD search process with trusted search engines for the identification of the best literature through critical appraisal to answer a clinical question. "For patients receiving orthodontic care, is an AI-generated treatment plan as likely to achieve acceptable outcomes?" Orthodontic treatment planning is a complex and time-consuming process that requires a high degree of expertise. Artificial intelligence (AI) has the potential to assist orthodontists in this process by automating some of the tasks involved, such as cephalometric analysis, surgery decisions, extraction decisions, and anchorage decisions.

A recent systematic …