Data Science Commons^™

Systematic Design And Data-Driven Evaluation Of Social Determinants Of Health Ontology (Sdoho), Yifang Dang, Fang Li, Xinyue Hu, Vipina K Keloth, Meng Zhang, Sunyang Fu, Muhammad F Amith, J Wilfred Fan, Jingcheng Du, Evan Yu, Hongfang Liu, Xiaoqian Jiang, Hua Xu, Cui Tao

Faculty, Staff and Student Publications

Objective: Social determinants of health (SDoH) play critical roles in health outcomes and well-being. Understanding the interplay of SDoH and health outcomes is critical to reducing healthcare inequalities and transforming a "sick care" system into a "health-promoting" system. To address the SDOH terminology gap and better embed relevant elements in advanced biomedical informatics, we propose an SDoH ontology (SDoHO), which represents fundamental SDoH factors and their relationships in a standardized and measurable way.

Material and methods: Drawing on the content of existing ontologies relevant to certain aspects of SDoH, we used a top-down approach to formally model classes, relationships, and …

The Development Of Artificial Intelligence-Based To Ols For Expert Peer Review Of Radiotherapy Treatment Plans, Mary Gronberg

Dissertations and Theses (Open Access)

Creating a patient-specific radiation treatment plan is a time-consuming and operator-dependent manual process. The treatment planner adjusts the planning parameters in a trial-and-error fashion in an effort to balance the competing clinical objectives of tumor coverage and normal tissue sparing. Often, a plan is selected because it meets basic organ at risk dose thresholds for severe toxicity; however, it is evident that a plan with a decreased risk of normal tissue complication probability could be achieved. This discrepancy between “acceptable” and “best possible” plan is magnified if either the physician or treatment planner lacks focal expertise in the disease site. …

Surface-Doped Zinc Gallate Colloidal Nanoparticles Exhibit Ph-Dependent Radioluminescence With Enhancement In Acidic Media, Navadeep Shrivastava, Jessa Guffie, Tamela L Moore, Burak Guzelturk, Amar S Kumbhar, Jianguo Wen, Zhiping Luo

Faculty, Staff and Student Publications

As abnormal acidic pH symbolizes dysfunctions of cells, it is highly desirable to develop pH-sensitive luminescent materials for diagnosing disease and imaging-guided therapy using high-energy radiation. Herein, we explored near-infrared-emitting Cr-doped zinc gallate ZnGa2O4 nanoparticles (NPs) in colloidal solutions with different pH levels under X-ray excitation. Ultrasmall NPs were synthesized via a facile hydrothermal method by controlling the addition of ammonium hydroxide precursor and reaction time, and structural characterization revealed Cr dopants on the surface of NPs. The synthesized NPs exhibited different photoluminescence and radioluminescence mechanisms, confirming the surface distribution of activators. It was observed that the colloidal NPs emit …

A Nurse-Led Telehealth Program For Diabetes Foot Care: Feasibility And Usability Study, Hsiao-Hui Ju, Rashmi Momin, Stanley Cron, Jed Jularbal, Jeffery Alford, Constance Johnson

Faculty, Staff and Student Publications

BACKGROUND: Diabetes mellitus can lead to severe and debilitating foot complications, such as infections, ulcerations, and amputations. Despite substantial progress in diabetes care, foot disease remains a major challenge in managing this chronic condition that causes serious health complications worldwide.

OBJECTIVE: The primary aim of this study was to examine the feasibility and usability of a telehealth program focused on preventive diabetes foot care. A secondary aim was to descriptively measure self-reported changes in diabetes knowledge, self-care, and foot care behaviors before and after participating in the program.

METHODS: The study used a single-arm, pre-post design in 2 large family …

Digital Health Technologies For Peripartum Depression Management Among Low-Socioeconomic Populations: Perspectives From Patients, Providers, And Social Media Channels, Alexandra Zingg, Tavleen Singh, Amy Franklin, Angela Ross, Sudhakar Selvaraj, Jerrie Refuerzo, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Peripartum Depression (PPD) affects approximately 10-15% of perinatal women in the U.S., with those of low socioeconomic status (low-SES) more likely to develop symptoms. Multilevel treatment barriers including social stigma and not having appropriate access to mental health resources have played a major role in PPD-related disparities. Emerging advances in digital technologies and analytics provide opportunities to identify and address access barriers, knowledge gaps, and engagement issues. However, most market solutions for PPD prevention and management are produced generically without considering the specialized needs of low-SES populations. In this study, we examine and portray the information and technology needs …

A Novel Integrated Approach To Predicting Cancer Immunotherapy Efficacy, Ruihan Luo, Jacqueline Chyr, Jianguo Wen, Yanfei Wang, Weiling Zhao, Xiaobo Zhou

Faculty, Staff and Student Publications

Immunotherapies have revolutionized cancer treatment modalities; however, predicting clinical response accurately and reliably remains challenging. Neoantigen load is considered as a fundamental genetic determinant of therapeutic response. However, only a few predicted neoantigens are highly immunogenic, with little focus on intratumor heterogeneity (ITH) in the neoantigen landscape and its link with different features in the tumor microenvironment. To address this issue, we comprehensively characterized neoantigens arising from nonsynonymous mutations and gene fusions in lung cancer and melanoma. We developed a composite NEO2IS to characterize interplays between cancer and CD8+ T-cell populations. NEO2IS improved prediction accuracy of patient responses to immune-checkpoint …

Comparative Analyses Define Differences Between Bhd-Associated Renal Tumour And Sporadic Chromophobe Renal Cell Carcinoma, Ryosuke Jikuya, Todd A Johnson, Kazuhiro Maejima, Jisong An, Young-Seok Ju, Hwajin Lee, Kyungsik Ha, Woojeung Song, Youngwook Kim, Yuki Okawa, Shota Sasagawa, Yuki Kanazashi, Masashi Fujita, Seiya Imoto, Taku Mitome, Shinji Ohtake, Go Noguchi, Sachi Kawaura, Yasuhiro Iribe, Kota Aomori, Tomoyuki Tatenuma, Mitsuru Komeya, Hiroki Ito, Yusuke Ito, Kentaro Muraoka, Mitsuko Furuya, Ikuma Kato, Satoshi Fujii, Haruka Hamanoue, Tomohiko Tamura, Masaya Baba, Toshio Suda, Tatsuhiko Kodama, Kazuhide Makiyama, Masahiro Yao, Brian M Shuch, Christopher J Ricketts, Laura S Schmidt, W Marston Linehan, Hidewaki Nakagawa, Hisashi Hasumi

Faculty, Staff and Student Publications

BACKGROUND: Birt-Hogg-Dubé (BHD) syndrome, caused by germline alteration of folliculin (FLCN) gene, develops hybrid oncocytic/chromophobe tumour (HOCT) and chromophobe renal cell carcinoma (ChRCC), whereas sporadic ChRCC does not harbor FLCN alteration. To date, molecular characteristics of these similar histological types of tumours have been incompletely elucidated.

METHODS: To elucidate renal tumourigenesis of BHD-associated renal tumours and sporadic renal tumours, we conducted whole genome sequencing (WGS) and RNA-sequencing (RNA-seq) of sixteen BHD-associated renal tumours from nine unrelated BHD patients, twenty-one sporadic ChRCCs and seven sporadic oncocytomas. We then compared somatic mutation profiles with FLCN variants and RNA expression profiles between BHD-associated …

The Integrative Studies On The Functional A-To-I Rna Editing Events In Human Cancers, Sijia Wu, Zhiwei Fan, Pora Kim, Liyu Huang, Xiaobo Zhou

Faculty, Staff and Student Publications

Adenosine-to-inosine (A-to-I) RNA editing, constituting nearly 90% of all RNA editing events in humans, has been reported to contribute to the tumorigenesis in diverse cancers. However, the comprehensive map for functional A-to-I RNA editing events in cancers is still insufficient. To fill this gap, we systematically and intensively analyzed multiple tumorigenic mechanisms of A-to-I RNA editing events in samples across 33 cancer types from The Cancer Genome Atlas. For individual candidate among ∼ 1,500,000 quantified RNA editing events, we performed diverse types of downstream functional annotations. Finally, we identified 24,236 potentially functional A-to-I RNA editing events, including the cases …

Genome-Wide Association Study Of Lung Adenocarcinoma In East Asia And Comparison With A European Population, Jianxin Shi, Kouya Shiraishi, Jiyeon Choi, Keitaro Matsuo, Tzu-Yu Chen, Juncheng Dai, Rayjean J Hung, Kexin Chen, Xiao-Ou Shu, Young Tae Kim, Maria Teresa Landi, Dongxin Lin, Wei Zheng, Zhihua Yin, Baosen Zhou, Bao Song, Jiucun Wang, Wei Jie Seow, Lei Song, I-Shou Chang, Wei Hu, Li-Hsin Chien, Qiuyin Cai, Yun-Chul Hong, Hee Nam Kim, Yi-Long Wu, Maria Pik Wong, Brian Douglas Richardson, Karen M Funderburk, Shilan Li, Tongwu Zhang, Charles Breeze, Zhaoming Wang, Batel Blechter, Bryan A Bassig, Jin Hee Kim, Demetrius Albanes, Jason Y Y Wong, Min-Ho Shin, Lap Ping Chung, Yang Yang, She-Juan An, Hong Zheng, Yasushi Yatabe, Xu-Chao Zhang, Young-Chul Kim, Neil E Caporaso, Jiang Chang, James Chung Man Ho, Michiaki Kubo, Yataro Daigo, Minsun Song, Yukihide Momozawa, Yoichiro Kamatani, Masashi Kobayashi, Kenichi Okubo, Takayuki Honda, Dean H Hosgood, Hideo Kunitoh, Harsh Patel, Shun-Ichi Watanabe, Yohei Miyagi, Haruhiko Nakayama, Shingo Matsumoto, Hidehito Horinouchi, Masahiro Tsuboi, Ryuji Hamamoto, Koichi Goto, Yuichiro Ohe, Atsushi Takahashi, Akiteru Goto, Yoshihiro Minamiya, Megumi Hara, Yuichiro Nishida, Kenji Takeuchi, Kenji Wakai, Koichi Matsuda, Yoshinori Murakami, Kimihiro Shimizu, Hiroyuki Suzuki, Motonobu Saito, Yoichi Ohtaki, Kazumi Tanaka, Tangchun Wu, Fusheng Wei, Hongji Dai, Mitchell J Machiela, Jian Su, Yeul Hong Kim, In-Jae Oh, Victor Ho Fun Lee, Gee-Chen Chang, Ying-Huang Tsai, Kuan-Yu Chen, Ming-Shyan Huang, Wu-Chou Su, Yuh-Min Chen, Adeline Seow, Jae Yong Park, Sun-Seog Kweon, Kun-Chieh Chen, Yu-Tang Gao, Biyun Qian, Chen Wu, Daru Lu, Jianjun Liu, Ann G Schwartz, Richard Houlston, Margaret R Spitz, Ivan P Gorlov, Xifeng Wu, Ping Yang, Stephen Lam, Adonina Tardon, Chu Chen, Stig E Bojesen, Mattias Johansson, Angela Risch, Heike Bickeböller, Bu-Tian Ji, H-Erich Wichmann, David C Christiani, Gadi Rennert, Susanne Arnold, Paul Brennan, James Mckay, John K Field, Sanjay S Shete, Loic Le Marchand, Geoffrey Liu, Angeline Andrew, Lambertus A Kiemeney, Shan Zienolddiny-Narui, Kjell Grankvist, Mikael Johansson, Angela Cox, Fiona Taylor, Jian-Min Yuan, Philip Lazarus, Matthew B Schabath, Melinda C Aldrich, Hyo-Sung Jeon, Shih Sheng Jiang, Jae Sook Sung, Chung-Hsing Chen, Chin-Fu Hsiao, Yoo Jin Jung, Huan Guo, Zhibin Hu, Laurie Burdett, Meredith Yeager, Amy Hutchinson, Belynda Hicks, Jia Liu, Bin Zhu, Sonja I Berndt, Wei Wu, Junwen Wang, Yuqing Li, Jin Eun Choi, Kyong Hwa Park, Sook Whan Sung, Li Liu, Chang Hyun Kang, Wen-Chang Wang, Jun Xu, Peng Guan, Wen Tan, Chong-Jen Yu, Gong Yang, Alan Dart Loon Sihoe, Ying Chen, Yi Young Choi, Jun Suk Kim, Ho-Il Yoon, In Kyu Park, Ping Xu, Qincheng He, Chih-Liang Wang, Hsiao-Han Hung, Roel C H Vermeulen, Iona Cheng, Junjie Wu, Wei-Yen Lim, Fang-Yu Tsai, John K C Chan, Jihua Li, Hongyan Chen, Hsien-Chih Lin, Li Jin, Jie Liu, Norie Sawada, Taiki Yamaji, Kathleen Wyatt, Shengchao A Li, Hongxia Ma, Meng Zhu, Zhehai Wang, Sensen Cheng, Xuelian Li, Yangwu Ren, Ann Chao, Motoki Iwasaki, Junjie Zhu, Gening Jiang, Ke Fei, Guoping Wu, Chih-Yi Chen, Chien-Jen Chen, Pan-Chyr Yang, Jinming Yu, Victoria L Stevens, Joseph F Fraumeni, Nilanjan Chatterjee, Olga Y Gorlova, Chao Agnes Hsiung, Christopher I Amos, Hongbing Shen, Stephen J Chanock, Nathaniel Rothman, Takashi Kohno, Qing Lan

Faculty, Staff and Student Publications

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European …

Mesoporous Silica Nanoparticles As A Gene Delivery Platform For Cancer Therapy, Nisar Ul Khaliq, Juyeon Lee, Joohyeon Kim, Yejin Kim, Sohyeon Yu, Jisu Kim, Sangwoo Kim, Daekyung Sung, Hyungjun Kim

Faculty, Staff and Student Publications

Cancer remains a major global health challenge. Traditional chemotherapy often results in side effects and drug resistance, necessitating the development of alternative treatment strategies such as gene therapy. Mesoporous silica nanoparticles (MSNs) offer many advantages as a gene delivery carrier, including high loading capacity, controlled drug release, and easy surface functionalization. MSNs are biodegradable and biocompatible, making them promising candidates for drug delivery applications. Recent studies demonstrating the use of MSNs for the delivery of therapeutic nucleic acids to cancer cells have been reviewed, along with their potential as a tool for cancer therapy. The major challenges and future interventions …

Multiparametric Magnetic Resonance Imaging Artificial Intelligence Pipeline For Oropharyngeal Cancer Radiotherapy Treatment Guidance, Kareem Wahid

Dissertations and Theses (Open Access)

Oropharyngeal cancer (OPC) is a widespread disease and one of the few domestic cancers that is rising in incidence. Radiographic images are crucial for assessment of OPC and aid in radiotherapy (RT) treatment. However, RT planning with conventional imaging approaches requires operator-dependent tumor segmentation, which is the primary source of treatment error. Further, OPC expresses differential tumor/node mid-RT response (rapid response) rates, resulting in significant differences between planned and delivered RT dose. Finally, clinical outcomes for OPC patients can also be variable, which warrants the investigation of prognostic models. Multiparametric MRI (mpMRI) techniques that incorporate simultaneous anatomical and functional information …

Automating The Radiation Therapy Treatment Planning Process For Pediatric Patients With Medulloblastoma, Soleil Hernandez

Dissertations and Theses (Open Access)

Over the past 50 years, pediatric cancer 5-year survival rates increased from 20% to 80% in high-income countries, however, these trends have not been mirrored in low-and-middle-income countries (LMICs). This is due in part to delayed diagnosis, higher rates of advanced disease at presentation and a growing lack of access to high quality medical personnel and technology necessary to deliver complex treatments.

The long-term goal of this study was to alleviate demanding workflows and increase global access to high-quality pediatric radiation therapy by harnessing the power of artificial intelligence to automate the radiation therapy treatment planning process for pediatric patients …

Learning In A Virtual Environment To Improve Type 2 Diabetes Outcomes: Randomized Controlled Trial, Constance M Johnson, Gail D'Eramo Melkus, Louise Reagan, Wei Pan, Sathya Amarasekara, Katherine Pereira, Nancy Hassell, Sarah Nowlin, Allison Vorderstrasse

Faculty, Staff and Student Publications

Background: Given the importance of self-management in type 2 diabetes mellitus (T2DM), a major aspect of health is providing diabetes self-management education and support. Known barriers include access, availability, and the lack of follow through on referral to education programs. Virtual education and support have increased in use over the last few years.

Objective: The purpose of the Diabetes Learning in a Virtual Environment (LIVE) study was to compare the effects of the LIVE intervention (educational 3D world) to a diabetes self-management education and support control website on diet and physical activity behaviors and behavioral and metabolic outcomes in adults …

The Potential Regulation Of A-To-I Rna Editing On Genes In Parkinson's Disease, Sijia Wu, Qiuping Xue, Xinyu Qin, Xiaoming Wu, Pora Kim, Jacqueline Chyr, Xiaobo Zhou, Liyu Huang

Faculty, Staff and Student Publications

Parkinson's disease (PD) is characterized by dopaminergic neurodegeneration and an abnormal accumulation of α-synuclein aggregates. A number of genetic factors have been shown to increase the risk of PD. Exploring the underlying molecular mechanisms that mediate PD's transcriptomic diversity can help us understand neurodegenerative pathogenesis. In this study, we identified 9897 A-to-I RNA editing events associated with 6286 genes across 372 PD patients. Of them, 72 RNA editing events altered miRNA binding sites and this may directly affect miRNA regulations of their host genes. However, RNA editing effects on the miRNA regulation of genes are more complex. They can (1) …

Quantitative Proteomic Screening Uncovers Candidate Diagnostic And Monitoring Serum Biomarkers Of Ankylosing Spondylitis, Mark Hwang, Shervin Assassi, Jim Zheng, Jessica Castillo, Reyna Chavez, Kamala Vanarsa, Chandra Mohan, John Reveille

Faculty, Staff and Student Publications

BACKGROUND: We sought to discover serum biomarkers of ankylosing spondylitis (AS) for diagnosis and monitoring disease activity.

METHODS: We studied biologic-treatment-naïve AS and healthy control (HC) patients' sera. Eighty samples matched by age, gender, and race (1:1:1 ratio) for AS patients with active disease, inactive disease, and HC were analyzed with SOMAscan™, an aptamer-based discovery platform. T-tests tests were performed for high/low-disease activity AS patients versus HCs (diagnosis) and high versus low disease activity (Monitoring) in a 2:1 and 1:1 ratio, respectively, to identify differentially expressed proteins (DEPs). We used the Cytoscape Molecular Complex Detection (MCODE) plugin to find clusters …

Distribution Of Serum Uric Acid Concentration And Its Association With Lipid Profiles: A Single-Center Retrospective Study In Children Aged 3 To 12 Years With Adenoid And Tonsillar Hypertrophy, Jiating Yu, Xin Liu, Honglei Ji, Yawei Zhang, Hanqiang Zhan, Ziyin Zhang, Jianguo Wen, Zhimin Wang

Faculty, Staff and Student Publications

BACKGROUND: Presently, there is no consensus regarding the optimal serum uric acid (SUA) concentration for pediatric patients. Adenoid and tonsillar hypertrophy is considered to be closely associated with pediatric metabolic syndrome and cardiovascular risk and is a common condition in children admitted to the hospital. Therefore, we aimed to evaluate the relationship between SUA and dyslipidemia and propose a reference range for SUA concentration that is associated with a healthy lipid profile in hospitalized children with adenoid and tonsillar hypertrophy.

METHODS: Preoperative data from 4922 children admitted for elective adenoidectomy and/or tonsillectomy surgery due to adenoid and tonsillar hypertrophy were …

Convolutional Neural Network For Biomarker Discovery For Triple Negative Breast Cancer With Rna Sequencing Data, Xiangning Chen, Justin M Balko, Fei Ling, Yabin Jin, Anneliese Gonzalez, Zhongming Zhao, Jingchun Chen

Faculty, Staff and Student Publications

Triple negative breast cancers (TNBCs) are tumors with a poor treatment response and prognosis. In this study, we propose a new approach, candidate extraction from convolutional neural network (CNN) elements (CECE), for discovery of biomarkers for TNBCs. We used the GSE96058 and GSE81538 datasets to build a CNN model to classify TNBCs and non-TNBCs and used the model to make TNBC predictions for two additional datasets, the cancer genome atlas (TCGA) breast cancer RNA sequencing data and the data from Fudan University Shanghai Cancer Center (FUSCC). Using correctly predicted TNBCs from the GSE96058 and TCGA datasets, we calculated saliency maps …

Genetic Correlations Between Alzheimer’S Disease And Gut Microbiome Genera, Davis Cammann, Yimei Lu, Melika J Cummings, Mark L Zhang, Joan Manuel Cue, Jenifer Do, Jeffrey Ebersole, Xiangning Chen, Edwin C Oh, Jeffrey L Cummings, Jingchun Chen

Faculty, Staff and Student Publications

A growing body of evidence suggests that dysbiosis of the human gut microbiota is associated with neurodegenerative diseases like Alzheimer's disease (AD) via neuroinflammatory processes across the microbiota-gut-brain axis. The gut microbiota affects brain health through the secretion of toxins and short-chain fatty acids, which modulates gut permeability and numerous immune functions. Observational studies indicate that AD patients have reduced microbiome diversity, which could contribute to the pathogenesis of the disease. Uncovering the genetic basis of microbial abundance and its effect on AD could suggest lifestyle changes that may reduce an individual's risk for the disease. Using the largest genome-wide …

Hemoglobin Concentration Impacts Viscoelastic Hemostatic Assays In Icu Admitted Patients, David J Roh, Tiffany R Chang, Aditya Kumar, Devin Burke, Glenda Torres, Katherine Xu, Winni Yang, Azzurra Cottarelli, Ernest Moore, Angela Sauaia, Kirk Hansen, Angela Velazquez, Amelia Boehme, Athina Vrosgou, Shivani Ghoshal, Soojin Park, Sachin Agarwal, Jan Claassen, E Sander Connolly, Gebhard Wagener, Richard O Francis, Eldad Hod

Faculty, Staff and Student Publications

Objectives: Low hemoglobin concentration impairs clinical hemostasis across several diseases. It is unclear whether hemoglobin impacts laboratory functional coagulation assessments. We evaluated the relationship of hemoglobin concentration on viscoelastic hemostatic assays in intracerebral hemorrhage (ICH) and perioperative patients admitted to an ICU.

Design: Observational cohort study and separate in vitro laboratory study.

Setting: Multicenter tertiary referral ICUs.

Patients: Two acute ICH cohorts receiving distinct testing modalities: rotational thromboelastometry (ROTEM) and thromboelastography (TEG), and a third surgical ICU cohort receiving ROTEM were evaluated to assess the generalizability of findings across disease processes and testing platforms. A separate in vitro ROTEM laboratory …

Machine Learning And Acute Stroke Imaging, Sunil A Sheth, Luca Giancardo, Marco Colasurdo, Visish M Srinivasan, Arash Niktabe, Peter Kan

Faculty, Staff and Student Publications

BACKGROUND: In recent years, machine learning (ML) has had notable success in providing automated analyses of neuroimaging studies, and its role is likely to increase in the future. Thus, it is paramount for clinicians to understand these approaches, gain facility with interpreting ML results, and learn how to assess algorithm performance.

OBJECTIVE: To provide an overview of ML, present its role in acute stroke imaging, discuss methods to evaluate algorithms, and then provide an assessment of existing approaches.

METHODS: In this review, we give an overview of ML techniques commonly used in medical imaging analysis and methods to evaluate performance. …

Readiness For Transfer: A Mixed-Methods Study On Icu Transfers Of Care, Soo-Hoon Lee, Clarice Wee, Phillip Phan, Yanika Kowitlawakul, Chee-Kiat Tan, Amartya Mukhopadhyay

Management Faculty Publications

Objective Past studies on intensive care unit (ICU) patient transfers compare the efficacy of using standardised checklists against unstructured communications. Less studied are the experiences of clinicians in enacting bidirectional (send/receive) transfers. This study reports on the differences in protocols and data elements between receiving and sending transfers in the ICU, and the elements constituting readiness for transfer.

Methods Mixed-methods study of a 574-bed general hospital in Singapore with a 74-bed ICU for surgical and medical patients. Six focus group discussions (FGDs) with 34 clinicians comprising 15 residents and 19 nurses, followed by a structured questionnaire survey of 140 clinicians …

Lessons Learned From Interdisciplinary Efforts To Combat Covid-19 Misinformation: Development Of Agile Integrative Methods From Behavioral Science, Data Science, And Implementation Science, Sahiti Myneni, Paula Cuccaro, Sarah Montgomery, Vivek Pakanati, Jinni Tang, Tavleen Singh, Olivia Dominguez, Trevor Cohen, Belinda Reininger, Lara S Savas, Maria E Fernandez

Faculty, Staff and Student Publications

BACKGROUND: Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals' preventive behaviors, including masking, testing, and vaccine uptake.

OBJECTIVE: In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation.

METHODS: We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a …

Machine Learning-Based Prediction Of Acute Mortality In Emergency Department Patients Using Twelve-Lead Electrocardiogram, Po-Cheng Chang, Zhi-Yong Liu, Yu-Chang Huang, Yu-Chun Hsu, Jung-Sheng Chen, Ching-Heng Lin, Richard Tsai, Chung-Chuan Chou, Ming-Shien Wen, Hung-Ta Wo, Wen-Chen Lee, Hao-Tien Liu, Chun-Chieh Wang, Chang-Fu Kuo

Faculty, Staff and Student Publications

BACKGROUND: The risk of mortality is relatively high among patients who visit the emergency department (ED), and stratifying patients at high risk can help improve medical care. This study aimed to create a machine-learning model that utilizes the standard 12-lead ECG to forecast acute mortality risk in ED patients.

METHODS: The database included patients who visited the EDs and underwent standard 12-lead ECG between October 2007 and December 2017. A convolutional neural network (CNN) ECG model was developed to classify survival and mortality using 12-lead ECG tracings acquired from 345,593 ED patients. For machine learning model development, the patients were …

Artificial Intelligence-Enabled Electrocardiographic Screening For Left Ventricular Systolic Dysfunction And Mortality Risk Prediction, Yu-Chang Huang, Yu-Chun Hsu, Zhi-Yong Liu, Ching-Heng Lin, Richard Tsai, Jung-Sheng Chen, Po-Cheng Chang, Hao-Tien Liu, Wen-Chen Lee, Hung-Ta Wo, Chung-Chuan Chou, Chun-Chieh Wang, Ming-Shien Wen, Chang-Fu Kuo

Faculty, Staff and Student Publications

BACKGROUND: Left ventricular systolic dysfunction (LVSD) characterized by a reduced left ventricular ejection fraction (LVEF) is associated with adverse patient outcomes. We aimed to build a deep neural network (DNN)-based model using standard 12-lead electrocardiogram (ECG) to screen for LVSD and stratify patient prognosis.

METHODS: This retrospective chart review study was conducted using data from consecutive adults who underwent ECG examinations at Chang Gung Memorial Hospital in Taiwan between October 2007 and December 2019. DNN models were developed to recognize LVSD, defined as LVEF

RESULTS: The mean age of patients in the testing dataset was 63.7 ± 16.3 years (46.3% …

Text Classification Of Cancer Clinical Trial Eligibility Criteria, Yumeng Yang, Soumya Jayaraj, Ethan Ludmir, Kirk Roberts

Faculty, Staff and Student Publications

Automatic identification of clinical trials for which a patient is eligible is complicated by the fact that trial eligibility are stated in natural language. A potential solution to this problem is to employ text classification methods for common types of eligibility criteria. In this study, we focus on seven common exclusion criteria in cancer trials: prior malignancy, human immunodeficiency virus, hepatitis B, hepatitis C, psychiatric illness, drug/substance abuse, and autoimmune illness. Our dataset consists of 764 phase III cancer trials with these exclusions annotated at the trial level. We experiment with common transformer models as well as a new pre-trained …

Transiently Impaired Endothelial Function During Thyroid Hormone Withdrawal In Differentiated Thyroid Cancer Patients, Li-Ying Hou, Xiao Li, Guo-Qiang Zhang, Chuang Xi, Chen-Tian Shen, Hong-Jun Song, Wen-Kun Bai, Zhong-Ling Qiu, Quan-Yong Luo

Faculty, Staff and Student Publications

PURPOSE: Endothelial dysfunction, which was associated with chronic hypothyroidism, was an early event in atherosclerosis. Whether short-term hypothyroidism following thyroxine withdrawal during radioiodine (RAI) therapy was associated with endothelial dysfunction in patients with differentiated thyroid cancer (DTC) was unclear. Aim of the study was to assess whether short-term hypothyroidism could impair endothelial function and the accompanied metabolic changes in the whole process of RAI therapy.

METHODS: We recruited fifty-one patients who underwent total thyroidectomy surgery and would accept RAI therapy for DTC. We analyzed thyroid function, endothelial function and serum lipids levels of the patients at three time points: the …

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 …

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 …

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 …