Data Science Commons^™

Segmentation Of Acute Stroke Infarct Core Using Image-Level Labels On Ct-Angiography, Luca Giancardo, Arash Niktabe, Laura Ocasio, Rania Abdelkhaleq, Sergio Salazar-Marioni, Sunil A Sheth

Faculty, Staff and Student Publications

Acute ischemic stroke is a leading cause of death and disability in the world. Treatment decisions, especially around emergent revascularization procedures, rely heavily on size and location of the infarct core. Currently, accurate assessment of this measure is challenging. While MRI-DWI is considered the gold standard, its availability is limited for most patients suffering from stroke. Another well-studied imaging modality is CT-Perfusion (CTP) which is much more common than MRI-DWI in acute stroke care, but not as precise as MRI-DWI, and it is still unavailable in many stroke hospitals. A method to determine infarct core using CT-Angiography (CTA), a much …

Keystroke-Dynamics For Parkinson's Disease Signs Detection In An At-Home Uncontrolled Population: A New Benchmark And Method, Shikha Tripathi, Teresa Arroyo-Gallego, Luca Giancardo

Faculty, Staff and Student Publications

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease disorder in the world. A prompt diagnosis would enable clinical trials for disease-modifying neuroprotective therapies. Recent research efforts have unveiled imaging and blood markers that have the potential to be used to identify PD patients promptly, however, the idiopathic nature of PD makes these tests very hard to scale to the general population. To this end, we need an easily deployable tool that would enable screening for PD signs in the general population. In this work, we propose a new set of features based on keystroke dynamics, i.e., the time …

Multidrug Resistance In The Standardized Treatment Of Colon Cancer Harboring A Rare Fibrosarcoma B-Type (Braf) Pn581i Mutation: A Case Report, Xiaoyan Wang, Chenyi Zhao, Yang Gong, Ying Wang, Feng Guo

Faculty, Staff and Student Publications

BRAF non-V600 mutations are a distinct molecular subset of colorectal cancer (CRC) that has little to no clinical similarity to the BRAF V600 mutations. It is generally considered that the BRAF non-V600 mutations correlate with better survival of CRC patients. In this report, we present an unusual case of that a midlife female patient who was initially diagnosed with stage IIIC colon cancer, and multiple metastases were found 25 months after radical surgery. Next-generation sequencing (NGS) revealed the BRAF p.N581I (c.1742A>T) mutation. She received chemotherapy, targeted therapy, and immunotherapy. However, the disease progressed rapidly with rare metastasis of the …

Annotation And Information Extraction Of Consumer-Friendly Health Articles For Enhancing Laboratory Test Reporting, Zhe He, Shubo Tian, Arslan Erdengasileng, Karim Hanna, Yang Gong, Zhan Zhang, Xiao Luo, Mia Liza A Lustria

Faculty, Staff and Student Publications

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in …

The Current Status And Future Prospects For Conversion Therapy In The Treatment Of Hepatocellular Carcinoma, Jinfeng Bai, Ming Huang, Bohan Song, Wei Luo, Rong Ding

Faculty, Staff and Student Publications

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide. In China, most HCC patients are diagnosed with advanced disease and in these cases surgery is challenging. Conversion therapy can be used to change unresectable HCC into resectable disease and is a potential breakthrough treatment strategy. The resection rate for unresectable advanced HCC has recently improved as a growing number of patients have benefited from conversion therapy. While conversion therapy is at an early stage of development, progress in patient selection, optimum treatment methods, and the timing of surgery have the potential to deliver significant benefits. In …

The Health-Promoting Effects And The Mechanism Of Intermittent Fasting, Simin Liu, Min Zeng, Weixi Wan, Ming Huang, Xiang Li, Zixian Xie, Shang Wang, Yu Cai

Faculty, Staff and Student Publications

Intermittent fasting (IF) is an eating pattern in which individuals go extended periods with little or no energy intake after consuming regular food in intervening periods. IF has several health-promoting effects. It can effectively reduce weight, fasting insulin levels, and blood glucose levels. It can also increase the antitumor activity of medicines and cause improvement in the case of neurological diseases, such as memory deficit, to achieve enhanced metabolic function and prolonged longevity. Additionally, IF activates several biological pathways to induce autophagy, encourages cell renewal, prevents cancer cells from multiplying and spreading, and delays senescence. However, IF has specific adverse …

Emulate Randomized Clinical Trials Using Heterogeneous Treatment Effect Estimation For Personalized Treatments: Methodology Review And Benchmark, Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Big data and (deep) machine learning have been ambitious tools in digital medicine, but these tools focus mainly on association. Intervention in medicine is about the causal effects. The average treatment effect has long been studied as a measure of causal effect, assuming that all populations have the same effect size. However, no "one-size-fits-all" treatment seems to work in some complex diseases. Treatment effects may vary by patient. Estimating heterogeneous treatment effects (HTE) may have a high impact on developing personalized treatment. Lots of advanced machine learning models for estimating HTE have emerged in recent years, but there has been …

Survey Of West Nile And Banzi Viruses In Mosquitoes, South Africa, 2011-2018, Caitlin Macintyre, Milehna Mara Guarido, Megan Amy Riddin, Todd Johnson, Leo Braack, Maarten Schrama, Erin Gorsich, Antonio Paulo Gouveia Almeida, Marietjie Venter

Faculty, Staff and Student Publications

We collected >40,000 mosquitoes from 5 provinces in South Africa during 2011-2018 and screened for zoonotic flaviviruses. We detected West Nile virus in mosquitoes from conservation and periurban sites and potential new mosquito vectors; Banzi virus was rare. Our results suggest flavivirus transmission risks are increasing in South Africa.

Modeling The Bidirectional Relationship Between Shared-Patient Physician Networks And Patient Longitudinal Treatment Patterns: Application To Physician Risky-Prescribing, Xin Ran

Dartmouth College Ph.D Dissertations

Risky-prescribing is a pressing public health concern in the United States. Opioids, benzodiazepines, and non-benzodiazepine sedative-hypnotics (sedative-hypnotics) are three commonly-prescribed but potentially risky drug groups, prescribed alone or in combination. Physician shared-patient networks provide a unique perspective in studying physician network characteristics and structures, as well as their association with the delivery of health care. Understanding how physician shared-patient networks are related to their prescribing may inform network-based interventions targeting risky-prescribing, which is yet to be fully studied.

We investigated patient receipt of risky prescriptions and physician risky-prescribing intensity through the scope of shared-patient networks. We used retrospective Medicare insurance …

Machine Learning Approach To Predict Tdcs-Induced Electric Current In The Human Brain, Chikako Olsen

Dissertations and Theses

Background: Transcranial direct current stimulation (tDCS) is a promising non-invasive method for treating neurological and psychiatric disorders and enhancing cognitive function. However, the underlying mechanisms of tDCS are not fully understood, and there is no ground truth for determining, non-invasively, where in the brain tDCS electrical currents flow. At the same time, effective neuronal engagement from tDCS requires accurate localization of the induced currents to specific brain target regions. Machine Learning (ML) has the potential to significantly improve the accuracy and precision of tDCS current prediction. This study aims to develop a novel approach using ML to predict the location …

Shallow Water Coral Distribution And Its Response To Climate Change, Amaury De Jesus

Dissertations and Theses

Shallow water corals are one of the main reef-building organisms that secrete carbonates as their skeletons, and therefore, are one of the major sinks of CO2 in the ocean. These reef builders are also very crucial to marine environments and human society. As the global energy demand continues rising, fossil fuel burning increases at a faster pace despite the increase in energy supply using clean and renewable energy. The increase of CO2 in the atmosphere has been shown to exacerbate global warming and may cause ocean acidification, threatening the habitat of shallow-water corals. Many recent observations show alarming signs of …

Dental Claires: Contrastive Language Image Retrieval Search For Dental Research, Tanjida Kabir, Luyao Chen, Muhammad F Walji, Luca Giancardo, Xiaoqian Jiang, Shayan Shams

Faculty, Staff and Student Publications

Learning about diagnostic features and related clinical information from dental radiographs is important for dental research. However, the lack of expert-annotated data and convenient search tools poses challenges. Our primary objective is to design a search tool that uses a user's query for oral-related research. The proposed framework,

Multimodal Neuron Classification Based On Morphology And Electrophysiology, Aqib Ahmad

Graduate Theses, Dissertations, and Problem Reports (ETD)

Categorizing neurons into different types to understand neural circuits and ultimately brain function is a major challenge in neuroscience. While electrical properties are critical in defining a neuron, its morphology is equally important. Advancements in single-cell analysis methods have allowed neuroscientists to simultaneously capture multiple data modalities from a neuron. We propose a method to classify neurons using both morphological structure and electrophysiology. Current approaches are based on a limited analysis of morphological features. We propose to use a new graph neural network to learn representations that more comprehensively account for the complexity of the shape of neuronal structures. In …

Longitudinal Sport Science Implementation In American Collegiate Men’S Basketball, Jason Stone

Graduate Theses, Dissertations, and Problem Reports (ETD)

The expanding opportunities to implement sport science frameworks in elite-level basketball environments coincide with the sport’s increasing global prominence. Concomitant to these opportunities is the continual growth of the sport technology market (e.g., wearables, force plates) and computational power (e.g., data management tools, coding capabilities), which yields solutions and challenges for both athletes and practitioners. Due to the rapid influx of new sport technologies in high performance environments, particularly American Collegiate Men’s Basketball, more formal and ecologically valid research on how to effectively utilize data derived from them, particularly over long periods of time (i.e., multiple seasons) is needed. To …

Invasive Buckthorn Mapping: A Uav-Based Approach Utilizing Machine Learning, Gis, And Remote Sensing Techniques In The Upper Peninsula Of Michigan, Vikranth Madeppa

Dissertations, Master's Theses and Master's Reports

An Invasive species is a species that is alien or non-native to the ecosystem which causes harm to economic, environmental, or human health (E.O. 13112 of Feb 3, 1999). Invasive species have posed a serious threat to ecosystems across the globe. These invasive species have impacts on the biodiversity and productivity of invaded forests. Remotely sensed data is a valuable resource for understanding and addressing issues related to invasive species. This study presents a novel approach for mapping the distribution of two invasive plant species, Common and Glossy Buckthorn, using unmanned aerial vehicles (UAVs), machine learning algorithms, geographic information systems …

Applying Data Science And Machine Learning To Understand Health Care Transition For Adolescents And Emerging Adults With Special Health Care Needs, Lisamarie Turk

Nursing ETDs

A problem of classification places adolescents and emerging adults with special health care needs among the most at risk for poor or life-threatening health outcomes. This preliminary proof-of-concept study was conducted to determine if phenotypes of health care transition (HCT) for this vulnerable population could be established. Such phenotypes could support development of future studies that require data classifications as input. Mining of electronic health record data and cluster analysis were implemented to identify phenotypes. Subsequently, a machine learning concept model was developed for predicting acute care and medical condition severity. Three clusters were identified and described (Cluster 1, n …

Influence Of Waist Circumference Measurement Site On Visceral Fat And Metabolic Risk In Youth, Sojung Lee, Yejin Kim, Minsub Han

Faculty, Staff and Student Publications

Although the rate of childhood obesity seems to have plateaued in recent years, the prevalence of obesity among children and adolescents remains high. Childhood obesity is a major public health concern as overweight and obese youth suffer from many co-morbid conditions once considered exclusive to adults. It is now well demonstrated that abdominal obesity as measured by waist circumference (WC) is an independent risk factor for cardiovascular disease and metabolic dysfunction in youth. Despite the strong associations between WC and cardiometabolic risk factors, there is no consensus regarding the optimal WC measurement sites to assess abdominal obesity and obesity-related health …

Collaborative Interprofessional Health Science Student Led Realistic Mass Casualty Incident Simulation, Deborah L Mccrea, Robert C Coghlan, Tiffany Champagne-Langabeer, Stanley Cron

Faculty, Staff and Student Publications

In collaboration, a health science university and a fire department offered a mass casualty incident (MCI) simulation. The purpose of this study was to evaluate a cross-section of student health care providers to determine their working knowledge of an MCI. Students were given a pretest using the Emergency Preparedness Information Questionnaire (EPIQ) and the Simple Triage and Rapid Transport (START) Quiz. The EPIQ instrument related to knowledge of triage, first aid, bio-agent detection, critical reporting, incident command, isolation/quarantine/decontamination, psychological issues, epidemiology, and communications. The START Quiz gave 10 scenarios. Didactic online content was given followed by the simulation a few …

Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, Samiksha Pachade, Ivan Coronado, Rania Abdelkhaleq, Juntao Yan, Sergio Salazar-Marioni, Amanda Jagolino, Charles Green, Mozhdeh Bahrainian, Roomasa Channa, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering …

Computer Clinical Decision Support That Automates Personalized Clinical Care: A Challenging But Needed Healthcare Delivery Strategy, Alan H Morris, Christopher Horvat, Brian Stagg, David W Grainger, Michael Lanspa, James Orme, Terry P Clemmer, Lindell K Weaver, Frank O Thomas, Colin K Grissom, Ellie Hirshberg, Thomas D East, Carrie Jane Wallace, Michael P Young, Dean F Sittig, Mary Suchyta, James E Pearl, Antinio Pesenti, Michela Bombino, Eduardo Beck, Katherine A Sward, Charlene Weir, Shobha Phansalkar, Gordon R Bernard, B Taylor Thompson, Roy Brower, Jonathon Truwit, Jay Steingrub, R Duncan Hiten, Douglas F Willson, Jerry J Zimmerman, Vinay Nadkarni, Adrienne G Randolph, Martha A Q Curley, Christopher J L Newth, Jacques Lacroix, Michael S D Agus, Kang Hoe Lee, Bennett P Deboisblanc, Frederick Alan Moore, R Scott Evans, Dean K Sorenson, Anthony Wong, Michael V Boland, Willard H Dere, Alan Crandall, Julio Facelli, Stanley M Huff, Peter J Haug, Ulrike Pielmeier, Stephen E Rees, Dan S Karbing, Steen Andreassen, Eddy Fan, Roberta M Goldring, Kenneth I Berger, Beno W Oppenheimer, E Wesley Ely, Brian W Pickering, David A Schoenfeld, Irena Tocino, Russell S Gonnering, Peter J Pronovost, Lucy A Savitz, Didier Dreyfuss, Arthur S Slutsky, James D Crapo, Michael R Pinsky, Brent James, Donald M Berwick

Faculty, Staff and Student Publications

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision …

Issues In Melanoma Detection: Semisupervised Deep Learning Algorithm Development Via A Combination Of Human And Artificial Intelligence, Xinyuan Zhang, Ziqian Xie, Yang Xiang, Imran Baig, Mena Kozman, Carly Stender, Luca Giancardo, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: Automatic skin lesion recognition has shown to be effective in increasing access to reliable dermatology evaluation; however, most existing algorithms rely solely on images. Many diagnostic rules, including the 3-point checklist, are not considered by artificial intelligence algorithms, which comprise human knowledge and reflect the diagnosis process of human experts.

OBJECTIVE: In this paper, we aimed to develop a semisupervised model that can not only integrate the dermoscopic features and scoring rule from the 3-point checklist but also automate the feature-annotation process.

METHODS: We first trained the semisupervised model on a small, annotated data set with disease and dermoscopic …

Advancing Access To Healthcare Through Telehealth: A Brownsville Community Assessment, Edna Ely-Ledesma, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

(1) Background: This paper focuses on the development of a community assessment for telehealth using an interprofessional lens, which sits at the intersection of public health and urban planning using multistakeholder input. The paper analyzes the process of designing and implementing a telemedicine plan for the City of Brownsville and its surrounding metros. (2) Methods: We employed an interprofessional approach to CBPR which assumed all stakeholders as equal partners alongside the researchers to uncover the most relevant and useful knowledge to inform the development of telehealth community assessment. (3) Results: Key findings include that: physicians do not have the technology, …

Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

In the U.S., 12.3% of children live with at least one parent who has a substance use disorder. Prior research has shown that men are more likely to seek treatment than women and that the barriers are different; however, there is limited research focusing specifically on opioid use disorder (OUD). We sought to understand the barriers and motivators for parents with OUD. We conducted a qualitative study by interviewing parents with OUD who were part of an outpatient treatment program. Interviews followed a semi-structured format with questions on access to and motivation for treatment. The interviews were recorded and transcribed …

Effect Of Temperature Cycling Pretreatment On The Thermal Stability Of Sm2(Co, Fe, Zr, Cu)17 Magnets In The Mild Temperature Range, Hulin Wu, Zhimei Long, Zhongsheng Li, Kaiqiang Song, Chaoqun Li, Dalong Cong, Bin Shao, Xiaowei Liu, Jianchun Sun, Yilong Ma

Faculty, Staff and Student Publications

The irredeemable magnetic losses of Sm(Co, Fe, Zr, Cu)7.8 permanent magnets caused by oxidation are very important for their practical application. In this work, the simulated results with R2 ≥ 98% based on the data of the temperature cycling test and the long-term isothermal test for the original samples confirmed that the magnetic flux losses reached 9.38% after the 5000th cycle in range R.T.–300 °C, and 7.15% after oxidated at 180 °C for 10 years, respectively. Demagnetization curves showed that the low-temperature oxidation mainly led to the remanence attenuation, while the coercivity remained relatively stable. SEM observation and EDS …

High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen

Faculty, Staff and Student Publications

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The …

Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss

All HCAS Student Capstones, Theses, and Dissertations

Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …

Open-Source Benchmarking Of Ibd Segment Detection Methods For Biobank-Scale Cohorts, Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of …

A Systematic Approach To Configuring Metamap For Optimal Performance, Xia Jing, Akash Indani, Nina Hubig, Hua Min, Yang Gong, James J Cimino, Dean F Sittig, Lior Rennert, David Robinson, Paul Biondich, Adam Wright, Christian Nøhr, Timothy Law, Arild Faxvaag, Ronald Gimbel

Faculty, Staff and Student Publications

BACKGROUND: MetaMap is a valuable tool for processing biomedical texts to identify concepts. Although MetaMap is highly configurative, configuration decisions are not straightforward.

OBJECTIVE: To develop a systematic, data-driven methodology for configuring MetaMap for optimal performance.

METHODS: MetaMap, the word2vec model, and the phrase model were used to build a pipeline. For unsupervised training, the phrase and word2vec models used abstracts related to clinical decision support as input. During testing, MetaMap was configured with the default option, one behavior option, and two behavior options. For each configuration, cosine and soft cosine similarity scores between identified entities and gold-standard terms were …

Intraoperative Localization And Preservation Of Reading In Ventral Occipitotemporal Cortex, Oscar Woolnough, Kathryn M Snyder, Cale W Morse, Meredith J Mccarty, Samden D Lhatoo, Nitin Tandon

Faculty, Staff and Student Publications

OBJECTIVE: Resective surgery in language-dominant ventral occipitotemporal cortex (vOTC) carries the risk of causing impairment to reading. Because it is not on the lateral surface, it is not easily accessible for intraoperative mapping, and extensive stimulation mapping can be time-consuming. Here the authors assess the feasibility of using task-based electrocorticography (ECoG) recordings intraoperatively to help guide stimulation mapping of reading in vOTC.

METHODS: In 11 patients undergoing extraoperative, intracranial seizure mapping, the authors recorded induced broadband gamma activation (70-150 Hz) during a visual category localizer. In 2 additional patients, whose pathologies necessitated resections in language-dominant vOTC, task-based functional mapping was …

Identifying Missing Is-A Relations In Orphanet Rare Disease Ontology, Maryamsadat Mohtashamian, Rashmie Abeysinghe, Xubing Hao, Licong Cui

Faculty, Staff and Student Publications

The Orphanet Rare Disease Ontology (ORDO) provides a structured vocabulary encapsulating rare diseases. Downstream applications of ORDO depend on its accuracy to effectively perform their tasks. In this paper, we implement an automated quality assurance pipeline to identify missing is-a relations in ORDO. We first obtain lexical features from concept names. Then we generate related and unrelated feature sharing concept-pairs, where a feature sharing concept-pair can further generate derived term-pairs. If an unrelated and related feature sharing concept-pair generate the same derived term-pair, then we suggest a potential missing is-a relation between the unrelated feature sharing concept-pair. Applying this approach …