Engineering Commons^™

Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D

Articles

Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …

An Ensemble Approach For Patient Prognosis Of Head And Neck Tumor Using Multimodal Data, Numan Saeed, Roba Al Majzoub, Ikboljon Sobirov, Mohammad Yaqub

Computer Vision Faculty Publications

Accurate prognosis of a tumor can help doctors provide a proper course of treatment and, therefore, save the lives of many. Tradi-tional machine learning algorithms have been eminently useful in crafting prognostic models in the last few decades. Recently, deep learning algorithms have shown significant improvement when developing diag-nosis and prognosis solutions to different healthcare problems. However, most of these solutions rely solely on either imaging or clinical data. Utilizing patient tabular data such as demographics and patient med-ical history alongside imaging data in a multimodal approach to solve a prognosis task has started to gain more interest recently and …

Childminding Professionalism And Professionalisation In Ireland: A Different Story, Miriam O'Regan, Ann Marie Halpenny, Noirin Hayes

Articles

This research focussed on documenting the praxis and paedagogy of paid, professional childminding (family childcare/day care) in Ireland. It explored professionalism and professionalisation among childminders in the context of the evolving understanding of professionalism in Early Childhood Education and Care (ECEC) nationally and internationally. The research was conducted within the framework of Ecocultural Theory (ECT) on the eve of mandatory regulation of childminding against the backdrop of Irish ECEC policy. A mixed method approach was adopted, using the Ecocultural Family Interview for Childminders (EFICh), including participants’ photographs, case study surveys, researcher field notes and holistic ratings. We present findings related …

Unsupervised Machine Learning For Pattern Identification In Occupational Accidents, Fatemeh Davoudi Kakhki, Steven Freeman, Gretchen Mosher

Faculty Research, Scholarly, and Creative Activity

Creating safe work environment is significant in saving workers’ lives, improving corporates’ social responsibility and sustainable development. Pattern identification in occupational accidents is vital in elaborating efficient safety counter-measures aiming at improving prevention and mitigating outcomes of future incidents. The objective of this study is to identify patterns related to the occurrence of occupational accidents in non-farm agricultural work environments based on workers’ compensation claims data, using latent class clustering method as an un-supervised machine learning modeling approach. The result showed injury profiles and incident dynamics have low, average, and high levels of risks based on the main causes and …

The Low Abundance Of Cpg In The Sars-Cov-2 Genome Is Not An Evolutionarily Signature Of Zap, Ali Afrasiabi, Hamid Alinejad-Rokny, Azad Khosh, Mostafa Rahnama, Nigel Lovell, Zhenming Xu, Diako Ebrahimi

Plant Pathology Faculty Publications

The zinc finger antiviral protein (ZAP) is known to restrict viral replication by binding to the CpG rich regions of viral RNA, and subsequently inducing viral RNA degradation. This enzyme has recently been shown to be capable of restricting SARS-CoV-2. These data have led to the hypothesis that the low abundance of CpG in the SARS-CoV-2 genome is due to an evolutionary pressure exerted by the host ZAP. To investigate this hypothesis, we performed a detailed analysis of many coronavirus sequences and ZAP RNA binding preference data. Our analyses showed neither evidence for an evolutionary pressure acting specifically on CpG …

Bladder Tumor In A Young Leukemic Patient Cured By Chemotherapy: A Case Report, Mohamed Tebaa, Mamoutou Dit Mody, Sylla Mahamadou, Mohamed Amine Lakmichi

Health Sciences

Adult bladder tumor is estimated to be the 10th most common tumor worldwide. However, its incidence is much less common in children. It is a disease of the elderly that peaks in the sixth decade of life. Nevertheless, bladder tumors could also affect children, adolescents, and young adults with a prevalence of

An Inkjet Printed Flexible Electrocorticography (Ecog) Microelectrode Array On A Thin Parylene-C Film, Yoontae Kim, Stella Alimperti, Paul Choi, Moses Noh

Electrical and Computer Engineering Faculty Publications

Electrocorticography (ECoG) is a conventional, invasive technique for recording brain signals from the cortical surface using an array of electrodes. In this study, we developed a highly flexible 22-channel ECoG microelectrode array on a thin Parylene film using novel fabrication techniques. Narrow (<40 >µm) and thin (<500 >nm) microelectrode patterns were first printed on PDMS, then the patterns were transferred onto Parylene films via vapor deposition and peeling. A custom-designed, 3D-printed connector was built and assembled with the Parylene-based flexible ECoG microelectrode array without soldering. The impedance of the assembled ECoG electrode array was measured in vitro by electrochemical impedance …

Prostacyclin Promotes Degenerative Pathology In A Model Of Alzheimer’S Disease, Tasha R. Womack, Craig T. Vollert, Odochi Ohia-Nwoko, Monika Schmitt, Saghi Montazari, Tina L. Beckett, David Mayerich, M. Paul Murphy, Jason L. Eriksen

Molecular and Cellular Biochemistry Faculty Publications

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is the most common form of dementia in aged populations. A substantial amount of data demonstrates that chronic neuroinflammation can accelerate neurodegenerative pathologies. In AD, chronic neuroinflammation results in the upregulation of cyclooxygenase and increased production of prostaglandin H2, a precursor for many vasoactive prostanoids. While it is well-established that many prostaglandins can modulate the progression of neurodegenerative disorders, the role of prostacyclin (PGI2) in the brain is poorly understood. We have conducted studies to assess the effect of elevated prostacyclin biosynthesis in a mouse model of AD. Upregulated prostacyclin expression …

Subomiembed: Self-Supervised Representation Learning Of Multi-Omics Data For Cancer Type Classification, Sayed Hashim, Muhammad Ali, Karthik Nandakumar, Mohammad Yaqub

Computer Vision Faculty Publications

For personalized medicines, very crucial intrinsic information is present in high dimensional omics data which is difficult to capture due to the large number of molecular features and small number of available samples. Different types of omics data show various aspects of samples. Integration and analysis of multi-omics data give us a broad view of tumours, which can improve clinical decision making. Omics data, mainly DNA methylation and gene expression profiles are usually high dimensional data with a lot of molecular features. In recent years, variational autoencoders (VAE) [13] have been extensively used in embedding image and text data into …

Characteristics And Assessing Biological Risks Of Airborne Bacteria In Waste Sorting Plant, Abbas Norouzian Baghani, Somayeh Golbaz, Gholamreza Ebrahimzadeh, Marcelo I. Guzman, Mahdieh Delikhoon, Mehdi Jamshidi Rastani, Abdullah Barkhordari, Ramin Nabizadeh

Chemistry Faculty Publications

Examining the concentration and types of airborne bacteria in waste paper and cardboard sorting plants (WPCSP) is an urgent matter to inform policy makers about the health impacts on exposed workers. Herein, we collected 20 samples at 9 points of a WPCSP every 6 winter days, and found that the most abundant airborne bacteria were positively and negatively correlated to relative humidity and temperature, respectively. The most abundant airborne bacteria (in units of CFU m⁻³) were: Staphylococcus sp. (72.4) > Micrococcus sp. (52.2) > Bacillus sp. (30.3) > Enterococcus sp. (24.0) > Serratia marcescens (20.1) > E. coli (19.1) > Pseudomonas sp. (16.0) > Nocardia …

Anesthetics Affect Peripheral Venous Pressure Waveforms And The Cross-Talk With Arterial Pressure, Ali Z. Al-Alawi, Kaylee R. Henry, Lauren D. Crimmins, Patrick C. Bonasso, Md Abul Hayat, Melvin S. Dassinger, Jeffrey M. Burford, Hanna K. Jensen, Joseph Sanford, Jingxian Wu, Kevin W. Sexton, Morten O. Jensen

Biomedical Engineering Faculty Publications and Presentations

Analysis of peripheral venous pressure (PVP) waveforms is a novel method of monitoring intravascular volume. Two pediatric cohorts were studied to test the effect of anesthetic agents on the PVP waveform and cross-talk between peripheral veins and arteries: (1) dehydration setting in a pyloromyotomy using the infused anesthetic propofol and (2) hemorrhage setting during elective surgery for craniosynostosis with the inhaled anesthetic isoflurane. PVP waveforms were collected from 39 patients that received propofol and 9 that received isoflurane. A multiple analysis of variance test determined if anesthetics influence the PVP waveform. A prediction system was built using k-nearest neighbor (k-NN) …

Essai Sur Le Terrain Du Mini Pipe Strain Meter Du Jniosh Comme Système D’Alerte De Sécurité Lors Des Travaux En Tranchée, André Lan, Bertrand Galy, Satoshi Tamate, Tomohito Hori, Nabutaka Hiraoka

Rapports de recherche scientifique

Les travaux en tranchée exposent les travailleurs à de nombreux risques. Le risque d'effondrement est le plus important et le plus fréquent lors de tels travaux, mais il est malheureusement très souvent sous-estimé, car même un effondrement mineur ou partiel de moins de 1 m3 de sol peut mortellement blesser un travailleur. L'analyse de 59 rapports de la Commission des normes, de l'équité, de la santé et de la sécurité du travail (CNESST) concernant des accidents graves et mortels survenus lors de travaux d'excavation et en tranchée réalisés entre juin 1973 et mai 2015 montre qu'il y a eu 51 …

Field Test Of The Jniosh Mini Pipe Strain Meter As A Safety Alert System During Trench Work, André Lan, Bertrand Galy, Satoshi Tamate, Tomohito Hori, Nabutaka Hiraoka

Rapports de recherche scientifique

Les travaux en tranchée exposent les travailleurs à de nombreux risques. Le risque d'effondrement est le plus important et le plus fréquent lors de tels travaux, mais il est malheureusement très souvent sous-estimé, car même un effondrement mineur ou partiel de moins de 1 m3 de sol peut mortellement blesser un travailleur. L'analyse de 59 rapports de la Commission des normes, de l'équité, de la santé et de la sécurité du travail (CNESST) concernant des accidents graves et mortels survenus lors de travaux d'excavation et en tranchée réalisés entre juin 1973 et mai 2015 montre qu'il y a eu 51 …

Applications Of Unsupervised Machine Learning In Autism Spectrum Disorder Research: A Review, Chelsea Parlett-Pelleriti, Elizabeth Stevens, Dennis R. Dixon, Erik J. Linstead

Engineering Faculty Articles and Research

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of …

Hyperparameter Optimization For Covid-19 Chest X-Ray Classification, Ibraheem Hamdi, Muhammad Ridzuan, Mohammad Yaqub

Computer Vision Faculty Publications

Despite the introduction of vaccines, Coronavirus disease (COVID-19) remains a worldwide dilemma, continuously developing new variants such as Delta and the recent Omicron. The current standard for testing is through polymerase chain reaction (PCR). However, PCRs can be expensive, slow, and/or inaccessible to many people. X-rays on the other hand have been readily used since the early 20th century and are relatively cheaper, quicker to obtain, and typically covered by health insurance. With a careful selection of model, hyperparameters, and augmentations, we show that it is possible to develop models with 83% accuracy in binary classification and 64% in multi-class …

Therapeutic Treatment With The Anti-Inflammatory Drug Candidate Mw151 May Partially Reduce Memory Impairment And Normalizes Hippocampal Metabolic Markers In A Mouse Model Of Comorbid Amyloid And Vascular Pathology, David J. Braun, David K. Powell, Christopher J. Mclouth, Saktimayee M. Roy, D. Martin Watterson, Linda J. Van Eldik

Neuroscience Faculty Publications

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, but therapeutic options are lacking. Despite long being able to effectively treat the ill-effects of pathology present in various rodent models of AD, translation of these strategies to the clinic has so far been disappointing. One potential contributor to this situation is the fact that the vast majority of AD patients have other dementia-contributing comorbid pathologies, the most common of which are vascular in nature. This situation is modeled relatively infrequently in basic AD research, and almost never in preclinical studies. As part of our efforts to develop …

Automatic Segmentation Of Head And Neck Tumor: How Powerful Transformers Are?, Ikboljon Sobirov, Otabek Nazarov, Hussain Alasmawi, Mohammad Yaqub

Computer Vision Faculty Publications

Cancer is one of the leading causes of death worldwide, and head and neck (H&N) cancer is amongst the most prevalent types. Positron emission tomography and computed tomography are used to detect and segment the tumor region. Clinically, tumor segmentation is extensively time-consuming and prone to error. Machine learning, and deep learning in particular, can assist to automate this process, yielding results as accurate as the results of a clinician. In this research study, we develop a vision transformers-based method to automatically delineate H&N tumor, and compare its results to leading convolutional neural network (CNN)-based models. We use multi-modal data …

Is It Possible To Predict Mgmt Promoter Methylation From Brain Tumor Mri Scans Using Deep Learning Models?, Numan Saeed, Shahad Hardan, Kudaibergen Abutalip, Mohammad Yaqub

Computer Vision Faculty Publications

Glioblastoma is a common brain malignancy that tends to occur in older adults and is almost always lethal. The effectiveness of chemotherapy, being the standard treatment for most cancer types, can be improved if a particular genetic sequence in the tumor known as MGMT promoter is methylated. However, to identify the state of the MGMT promoter, the conventional approach is to perform a biopsy for genetic analysis, which is time and effort consuming. A couple of recent publications proposed a connection between the MGMT promoter state and the MRI scans of the tumor and hence suggested the use of deep …

Highly-Individualized Physical Therapy Instruction Beyond The Clinic Using Wearable Inertial Sensors, Samir A. Rawashdeh, Ella Reimann, Timothy L. Uhl

Physical Therapy Faculty Publications

Musculoskeletal conditions, often requiring rehabilitation, affect one-third of the U.S. population annually. This paper presents rehabilitation assistive technology that includes body-worn motion sensors and a mobile application that extends the reach of a physical rehabilitation specialist beyond the clinic to ensure that home exercises are performed with the same precision as under clinical supervision. Assisted by a specialist in the clinic, the wearable sensors and user interface developed allow the capture of individualized exercises unique to the patient’s physical abilities. Beyond the clinical setting, the system can assist patients by providing real-time corrective feedback to repeat these exercises through a …

Inpatient Discharge-By-Noon: Are Fewer Better Than All?, Nicholas Ballester, Pratik J. Parikh, Kara Combs, Jordan S. Peck

Journal of Maine Medical Center

Introduction: To address boarding in hospital emergency departments, discharge-by-noon could free up inpatient beds earlier in the day. However, discharging all patients by noon can heavily burden inpatient units and may not be feasible. In this study, we determine the number of discharges after which the benefits of an additional discharge-by-noon diminish.

Methods: We conducted a simulation analysis to quantify how occupancy rate, mean daily number of discharges, and peak discharge time impact upstream boarding time in an inpatient neurology unit at Maine Medical Center. Using a day-of-discharge simulation model with one year of retrospective data, we assessed configurations approximating …

Transcranial Direct Current Stimulation On Parkinson’S Disease: Systematic Review And Meta-Analysis, Paloma Cristina Alves De Oliveira, Thiago Anderson Brito De Araújo, Daniel Gomes Da Silva Machado, Abner Cardoso Rodrigues, Marom Bikson, Suellen Marinho Andrade, Alexandre Hideki Okano, Hougelle Simplicio, Rodrigo Pegado, Edgard Morya

Publications and Research

Background: Clinical impact of transcranial direct current stimulation (tDCS) alone for Parkinson’s disease (PD) is still a challenge. Thus, there is a need to synthesize available results, analyze methodologically and statistically, and provide evidence to guide tDCS in PD.

Objective: Investigate isolated tDCS effect in different brain areas and number of stimulated targets on PD motor symptoms.

Methods: A systematic review was carried out up to February 2021, in databases: Cochrane Library, EMBASE, PubMed/MEDLINE, Scopus, and Web of science. Full text articles evaluating effect of active tDCS (anodic or cathodic) vs. sham or control on motor symptoms of PD were …

Magnetic Nanoparticles Enhanced Surface Plasmon Resonance Biosensor For Rapid Detection Of Salmonella Typhimurium In Romaine Lettuce, Devendra Bhandari, Fur-Chi Chen, Roger C. Bridgman

Human Sciences Faculty Research

Salmonella is one of the major foodborne pathogens responsible for many cases of illnesses, hospitalizations and deaths worldwide. Although different methods are available to timely detect Salmonella in foods, surface plasmon resonance (SPR) has the benefit of real-time detection with a high sensitivity and specificity. The purpose of this study was to develop an SPR method in conjunction with magnetic nanoparticles (MNPs) for the rapid detection of Salmonella Typhimurium. The assay utilizes a pair of well-characterized, flagellin-specific monoclonal antibodies; one is immobilized on the sensor surface and the other is coupled to the MNPs. Samples of romaine lettuce contaminated with …

Glycocalyx Mechanotransduction Mechanisms Are Involved In Renal Cancer Metastasis, Heriberto Moran, Limary M. Cancel, Peigen Huang, Sylvie Roberge, Tuoye Xu, John M. Tarbell, Lance L. Munn

Publications and Research

Mammalian cells, including cancer cells, are covered by a surface layer containing cell bound proteoglycans, glycoproteins, associated glycosaminoglycans and bound proteins that is commonly referred to as the glycocalyx. Solid tumors also have a dynamic fluid microenvironment with elevated interstitial flow. In the present work we further investigate the hypothesis that interstitial flow is sensed by the tumor glycocalyx leading to activation of cell motility and metastasis. Using a highly metastatic renal carcinoma cell line (SN12L1) and its low metastatic counterpart (SN12C) we demonstrate in vitro that the small molecule Suberoylanilide Hydroxamic Acid (SAHA) inhibits the heparan sulfate synthesis enzyme …

Optimizing Biomedical Discoveries As An Engine Of Culture Change In An Academic Medical Center, Anne K. Dechant, Stephen Fening, Michael Haag, William Harte, Mark R. Chance

Faculty Scholarship

Academic discovery in biomedicine is a growing enterprise with tens of billions of dollars in research funding available to universities and hospitals. Protecting and optimizing the resultant intellectual property is required in order for the discoveries to have an impact on society. To achieve that, institutions must create a multidisciplinary, collaborative system of review and support, and utilize connections to industry partners. In this study, we outline the efforts of Case Western Reserve University, coordinated through its Clinical and Translational Science Collaborative (CTSC), to promote entrepreneurial culture, and achieve goals of product development and startup formation for biomedical and population …

Toward A Multimodal Computer-Aided Diagnostic Tool For Alzheimer’S Disease Conversion, Danilo Pena, Jessika Suescun, Mya Schiess, Timothy M. Ellmore, Luca Giancardo, Alzheimer’S Disease Neuroimaging Initiative

Publications and Research

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder. It is one of the leading sources of morbidity and mortality in the aging population AD cardinal symptoms include memory and executive function impairment that profoundly alters a patient’s ability to perform activities of daily living. People with mild cognitive impairment (MCI) exhibit many of the early clinical symptoms of patients with AD and have a high chance of converting to AD in their lifetime. Diagnostic criteria rely on clinical assessment and brain magnetic resonance imaging (MRI). Many groups are working to help automate this process to improve the clinical workflow. Current …

Icu Liberation: Early Mobility And Exercise, Leann Volkers, Holly Kockler, Kristi Patterson

Nursing Posters

The aim of this project was to streamline and standardize the delivery of the follow up Important Message from Medicare (IMM) for IP admissions across CC and Carris-RWF in compliance with regulatory standards of care.

Key drivers identified:

• Site specific variation
• Underutilization of Epic functionality
• Use of data to understand performance

Design And Development Of Magnetic Iron Core Gold Nanoparticle-Based Fluorescent Multiplex Assay To Detect Salmonella, Xinyi Zhao

Articles

Salmonella is a bacterial pathogen which is one of the leading causes of severe illnesses in humans. The current study involved the design and development of two methods, respectively using iron oxide nanoparticle (IONP) and iron core gold nanoparticle (ICGNP), conjugated with the Salmonella antibody and the fluorophore, 4-Methylumbelliferyl Caprylate (4-MUCAP), used as an indicator, for its selective and sensitive detection in contaminated food products. Twenty double-blind beverage samples, spiked with Salmonella enteritidis, Staphylococcus aureus, and Escherichia coli, were prepared in sterile Eppendorf® tubes at room temperature. The gold layer and spikes of ICGNPs increased the surface areas. The ratio …

Exploring The Concept Of The Digital Educator During Covid-19, Fernando Jimenez, Gracia Sanchez, Jose Palma, Luis Miralles-Pechuán, Juan A. Botia

Articles

T In many machine learning classification problems, datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes, eliminating the redundant and irrelevant ones. Due to the huge size of the search space of the possible solutions, the attribute subset evaluation feature selection methods are not very suitable, so in these scenarios feature ranking methods are used. Most of the feature ranking methods described in the literature are univariate methods, which do not detect interactions between factors. In this paper, we propose two new multivariate feature ranking methods based on …

Optimization Of An Automated Algorithm For Analysis Of Spontaneous Rhythmic Bladder Contractions During Urodynamics Testing, Isabelle Pummill, Rui Li, Zachary Cullingsworth, Adam Klausner, John Speich

Summer REU Program

No abstract provided.

Quantitative Sustainable Design (Qsd) For The Prioritization Of Research, Development, And Deployment Of Technologies: A Tutorial And Review, Yalin Li, John T. Trimmer, Steven Hand, Xinyi Zhang, Katherine G. Chambers, Hannah A. C. Lohman, Rui Shi, Diana M. Byrne, Sherri M. Cook, Jeremy S. Guest

UK CARES Faculty Publications

The pursuit of sustainability has catalyzed broad investment in the research, development, and deployment (RD&D) of innovative water, sanitation, and resource recovery technologies, yet the lack of transparent and agile methodologies to navigate the expansive landscape of technology development pathways remains a critical challenge. This challenge is further complicated by the higher levels of uncertainty that are intrinsic to early-stage technologies. In this work, we review and synthesize published literature on the sustainability analyses of water and related technologies to present quantitative sustainable design (QSD) – a methodology to expedite and support technology RD&D. With a shared lexicon and a …