Medicine and Health Sciences Commons^™

Large Language Models For Healthcare Data Augmentation: An Example On Patient-Trial Matching, Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

Faculty, Staff and Student Publications

The process of matching patients with suitable clinical trials is essential for advancing medical research and providing optimal care. However, current approaches face challenges such as data standardization, ethical considerations, and a lack of interoperability between Electronic Health Records (EHRs) and clinical trial criteria. In this paper, we explore the potential of large language models (LLMs) to address these challenges by leveraging their advanced natural language generation capabilities to improve compatibility between EHRs and clinical trial descriptions. We propose an innovative privacy-aware data augmentation approach for LLM-based patient-trial matching (LLM-PTM), which balances the benefits of LLMs while ensuring the security …

Split Learning For Distributed Collaborative Training Of Deep Learning Models In Health Informatics, Zhuohang Li, Chao Yan, Xinmeng Zhang, Gharib Gharibi, Zhijun Yin, Xiaoqian Jiang, Bradley A Malin

Faculty, Staff and Student Publications

Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generalize across healthcare organizations is challenging. This is due, in part, to the inherent siloed nature of these organizations and patient privacy requirements. To address this problem, we illustrate how split learning can enable collaborative training of deep learning models across disparate and privately maintained health datasets, while keeping the original records and model parameters private. We introduce a new privacy-preserving distributed learning framework that offers a higher level of privacy compared to conventional federated learning. We …

A Scientific Communication Mentoring Intervention Benefits Diverse Mentees With Language Variety Related Discomfort, Carrie A Cameron, Hwa Young Lee, Cheryl B Anderson, Erin K Dahlstrom, Shine Chang

Faculty, Staff and Student Publications

We studied social-psychological effects over time of a faculty-mentor workshop intervention that addressed attitudes associated with language variety and their impact on scientific communication (SC) skill development of PhD and postdoctoral STEM research trainees (N = 274). Six months after their mentors attended the workshop, all mentees had significant gains in productivity in speaking tasks. In particular, mentees with high language discomfort rated their quality of communication with their mentor and their enthusiasm about communicating more highly (p < .05 for both measures), compared to mentees with low language discomfort. In addition, mentees raised speaking nonstandardized varieties of English reported significant reductions in discomfort related to language use (p = .003), compared to mentees raised speaking standardized English. We conclude that training mentors to understand and respond to …

Integrating Comorbidity Knowledge For Alzheimer's Disease Drug Repurposing Using Multi-Task Graph Neural Network, Ko-Hong Lin, Kang-Lin Hsieh, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Alzheimer's Disease (AD) is a multifactorial disease that shares common etiologies with its multiple comorbidities, especially vascular diseases. To predict repurposable drugs for AD utilizing the relatively well-investigated comorbidities' knowledge, we proposed a multi-task graph neural network (GNN)-based pipeline that incorporates the corresponding biomedical interactome of these diseases with their genetic markers and effective therapeutics. Our pipeline can accurately capture the interactions and disease classification in the network. Next, we predicted drugs that might interact with the AD module by the node embedding similarity. Our candidates are mostly BBB permeable, and literature evidence showed their potential for treating AD pathologies, …

Local Contrastive Learning For Medical Image Recognition, Syed A Rizvi, Ruixiang Tang, Xiaoqian Jiang, Xiaotian Ma, Xia Hu

Faculty, Staff and Student Publications

The proliferation of Deep Learning (DL)-based methods for radiographic image analysis has created a great demand for expert-labeled radiology data. Recent self-supervised frameworks have alleviated the need for expert labeling by obtaining supervision from associated radiology reports. These frameworks, however, struggle to distinguish the subtle differences between different pathologies in medical images. Additionally, many of them do not provide interpretation between image regions and text, making it difficult for radiologists to assess model predictions. In this work, we propose Local Region Contrastive Learning (LRCLR), a flexible fine-tuning framework that adds layers for significant image region selection as well as cross-modality …

School-Based Intervention Impacts Availability Of Vegetables And Beverages In Participants’ Homes, Erin A Hudson, Marissa Burgermaster, Sophia M Isis, Matthew R Jeans, Sarvenaz Vandyousefi, Matthew J Landry, Rebecca Seguin-Fowler, Joya Chandra, Jaimie Davis

Faculty, Staff and Student Publications

As rates of metabolic syndrome rise, children consume too few vegetables and too much added sugar. Because children tend to eat what is available at home, the home environment plays a key role in shaping dietary habits. This secondary analysis evaluated the effects of a school-based gardening, cooking, and nutrition education intervention (TX Sprouts) compared to control on the availability of vegetables, fruit juice, and sugar-sweetened beverages (SSBs) at home. In the TX Sprouts cluster-randomized trial, 16 schools were randomized to TX Sprouts (

Comparison Of Pharmacological Inhibitors Of Lysine-Specific Demethylase 1 In Glioblastoma Stem Cells Reveals Inhibitor-Specific Efficacy Profiles, Lea M Stitzlein, Achintyan Gangadharan, Leslie M Walsh, Deokhwa Nam, Alexsandra B Espejo, Melissa M Singh, Kareena H Patel, Yue Lu, Xiaoping Su, Ravesanker Ezhilarasan, Joy Gumin, Sanjay Singh, Erik Sulman, Frederick F Lang, Joya Chandra

Faculty, Staff and Student Publications

INTRODUCTION: Improved therapies for glioblastoma (GBM) are desperately needed and require preclinical evaluation in models that capture tumor heterogeneity and intrinsic resistance seen in patients. Epigenetic alterations have been well documented in GBM and lysine-specific demethylase 1 (LSD1/KDM1A) is amongst the chromatin modifiers implicated in stem cell maintenance, growth and differentiation. Pharmacological inhibition of LSD1 is clinically relevant, with numerous compounds in various phases of preclinical and clinical development, but an evaluation and comparison of LSD1 inhibitors in patient-derived GBM models is lacking.

METHODS: To assess concordance between knockdown of LSD1 and inhibition of LSD1 using a prototype inhibitor in …

Immune Checkpoint Inhibitors In Advanced Cutaneous Squamous Cell Carcinoma: A Systemic Review And Meta-Analysis, Haoran Zhang, Ai Zhong, Junjie Chen

Faculty, Staff and Student Publications

BACKGROUND: To evaluate the immune checkpoint inhibitors (CPI) for the treatment of patients with advanced cutaneous squamous cell carcinoma (CSCC).

MATERIALS AND METHODS: A meta-analysis was conducted, and the efficacy and safety of CPI were assessed.

RESULTS: A total of 13 studies with 980 patients were included. The pooled objective response rate (ORR) and disease control rate were 47.2% and 64.4%, separately. In addition, patients with primary tumor located in head and neck (odds ratio [OR]: 0.374, 95% confidence interval [CI]: 0.219-0.640, p < 0.001) and positive expression of programmed death ligand 1 (OR: 0.364, 95% CI: 0.158-0.842, P = 0.018) had superior ORR during CPI treatment. The incidence of progression free survival at 6 and 12 months was 59.3% and 52.8%, and 80.6% and 76.4% for overall survival. As for safety, the overall incidence of adverse events with all grades and 3-4 grade was 76.9% and 20.2%.

CONCLUSIONS: Our systematic review confirmed the satisfying efficacy and acceptable toxicity of CPI for advanced CSCC.

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 …

Sart-3 Functions To Regulate Germline Sex Determination In C Elegans, Tokiko Furuta, Swathi Arur

Faculty, Staff and Student Publications

Caenorhabditis elegans gene sart-3 was first identified as the homolog of human SART3 ( S quamous cell carcinoma A ntigen R ecognized by T -cells 3). In humans, expression of SART3 is associated with squamous cell carcinoma, thus most of the studies focus on its potential role as a target of cancer immunotherapy (Shichijo et al. 1998; Yang et al. 1999). Furthermore, SART3 is also known as Tip110 (Liu et al. 2002; Whitmill et al. 2016) in the context of HIV virus host activation pathway. Despite these disease related studies, the molecular function of this protein was not revealed until …

Optimization Of Mesh Generation For Geometric Accuracy, Robustness, And Efficiency Of Biomechanical-Model-Based Deformable Image Registration, Yulun He, Brian M Anderson, Guillaume Cazoulat, Bastien Rigaud, Lusmeralis Almodovar-Abreu, Julianne Pollard-Larkin, Peter Balter, Zhongxing Liao, Radhe Mohan, Bruno Odisio, Stina Svensson, Kristy K Brock

Faculty, Staff and Student Publications

BACKGROUND: Successful generation of biomechanical-model-based deformable image registration (BM-DIR) relies on user-defined parameters that dictate surface mesh quality. The trial-and-error process to determine the optimal parameters can be labor-intensive and hinder DIR efficiency and clinical workflow.

PURPOSE: To identify optimal parameters in surface mesh generation as boundary conditions for a BM-DIR in longitudinal liver and lung CT images to facilitate streamlined image registration processes.

METHODS: Contrast-enhanced CT images of 29 colorectal liver cancer patients and end-exhale four-dimensional CT images of 26 locally advanced non-small cell lung cancer patients were collected. Different combinations of parameters that determine the triangle mesh quality …

Head And Neck Radiation Therapy Patterns Of Practice Variability Identified As A Challenge To Real-World Big Data: Results From The Learning From Analysis Of Multicentre Big Data Aggregation (Lambda) Consortium, Amanda Caissie, Michelle Mierzwa, Clifton David Fuller, Murali Rajaraman, Alex Lin, Andrew Macdonald, Richard Popple, Ying Xiao, Lisanne Vandijk, Peter Balter, Helen Fong, Heping Xu, Matthew Kovoor, Joonsang Lee, Arvind Rao, Mary Martel, Reid Thompson, Brandon Merz, John Yao, Charles Mayo

Faculty, Staff and Student Publications

PURPOSE: Outside of randomized clinical trials, it is difficult to develop clinically relevant evidence-based recommendations for radiation therapy (RT) practice guidelines owing to lack of comprehensive real-world data. To address this knowledge gap, we formed the Learning from Analysis of Multicenter Big Data Aggregation consortium to cooperatively implement RT data standardization, develop software solutions for data analysis, and recommend clinical practice change based on real-world data analyzed. The first phase of this "Big Data" study aimed at characterizing variability in clinical practice patterns of dosimetric data for organs at risk (OARs) that would undermine subsequent use of large-scale, electronically aggregated …

A Novel Nih Research Grant Recommender Using Bert, Jie Zhu, Braja Gopal Patra, Hulin Wu, Ashraf Yaseen

Faculty, Staff and Student Publications

Research grants are important for researchers to sustain a good position in academia. There are many grant opportunities available from different funding agencies. However, finding relevant grant announcements is challenging and time-consuming for researchers. To resolve the problem, we proposed a grant announcements recommendation system for the National Institute of Health (NIH) grants using researchers' publications. We formulated the recommendation as a classification problem and proposed a recommender using state-of-the-art deep learning techniques: i.e. Bidirectional Encoder Representations from Transformers (BERT), to capture intrinsic, non-linear relationship between researchers' publications and grants announcements. Internal and external evaluations were conducted to assess the …

Data Mining Pipeline For Covid-19 Vaccine Safety Analysis Using A Large Electronic Health Record, Yan Huang, Xiaojin Li, Deepa Dongarwar, Hulin Wu, Guo-Qiang Zhang

Faculty, Staff and Student Publications

We developed a novel data mining pipeline that automatically extracts potential COVID-19 vaccine-related adverse events from a large Electronic Health Record (EHR) dataset. We applied this pipeline to Optum® de-identified COVID-19 EHR dataset containing COVID-19 vaccine records between December 11, 2020 and January 20, 2022. We compared post-vaccination diagnoses between the COVID-19 vaccine group and the influenza vaccine group among 553,682 individuals without COVID-19 infection. We extracted 1,414 ICD-10 diagnosis categories (first three ICD10 digits) within 180 days after the first dose of the COVID-19 vaccine. We then ranked the diagnosis codes using the adverse event rates and adjusted odds …

Dose Escalation For Pancreas Sbrt: Potential And Limitations Of Using Daily Online Adaptive Radiation Therapy And An Iterative Isotoxicity Automated Planning Approach, Dong Joo Rhee, Sam Beddar, Joseph Abi Jaoude, Gabriel Sawakuchi, Rachael Martin, Luis Perles, Cenji Yu, Yulun He, Laurence E Court, Ethan B Ludmir, Albert C Koong, Prajnan Das, Eugene J Koay, Cullen Taniguichi, Joshua S Niedzielski

Faculty, Staff and Student Publications

PURPOSE: To determine the dosimetric limitations of daily online adaptive pancreas stereotactic body radiation treatment by using an automated dose escalation approach.

METHODS AND MATERIALS: We collected 108 planning and daily computed tomography (CT) scans from 18 patients (18 patients × 6 CT scans) who received 5-fraction pancreas stereotactic body radiation treatment at MD Anderson Cancer Center. Dose metrics from the original non-dose-escalated clinical plan (non-DE), the dose-escalated plan created on the original planning CT (DE-ORI), and the dose-escalated plan created on daily adaptive radiation therapy CT (DE-ART) were analyzed. We developed a dose-escalation planning algorithm within the radiation treatment …

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 …

Revisiting The Type Species Of The Genus Homidia (Collembola, Entomobryidae), Guo-Qiang Zhang, Yu-Xin Zhao, Feng Zhang

Faculty, Staff and Student Publications

Homidiacingula Börner, 1906, the type species of the genus Homidia Börner, 1906, is widespread from India to Southeast Asia, but its detailed morphological characteristics have not yet been described. We examined the morphology of specimens of H.cingula from Indonesia and southwestern China and confirmed their conspecific status by comparing their DNA barcoding sequences. We also compared the morphology of H.cingula with other two closely related species, confirming the valid species status of H.subcingula Denis, 1948. Our study provides new taxonomic and molecular data for the genus Homidia.

Extreme Temperatures And Sickness Absence In The Mediterranean Province Of Barcelona: An Occupational Health Issue, Mireia Utzet, Amaya Ayala-Garcia, Fernando G Benavides, Xavier Basagaña

Faculty, Staff and Student Publications

OBJECTIVES: This study aims to assess the association between daily temperature and sickness absence episodes in the Mediterranean province of Barcelona between 2012 and 2015, according to sociodemographic and occupational characteristics.

METHODS: Ecological study of a sample of salaried workers affiliated to the Spanish social security, resident in Barcelona province between 2012 and 2015. The association between daily mean temperature and risk of new sickness absence episodes was estimated with distributed lag non-linear models. The lag effect up to 1 week was considered. Analyses were repeated separately by sex, age groups, occupational category, economic sector and medical diagnosis groups of …

Selection And Validation Of Optimal Reference Genes For Rt-Qpcr Analyses In Aphidoletes Aphidimyza Rondani (Diptera: Cecidomyiidae), Xiu-Xian Shen, Guo-Qiang Zhang, Yu-Xin Zhao, Xiao-Xiao Zhu, Xiao-Fei Yu, Mao-Fa Yang, Feng Zhang

Faculty, Staff and Student Publications

Aphidoletes aphidimyza is a predator that is an important biological agent used to control agricultural and forestry aphids. Although many studies have investigated its biological and ecological characteristics, few molecular studies have been reported. The current study was performed to identify suitable reference genes to facilitate future gene expression and function analyses via quantitative reverse transcription PCR. Eight reference genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), RPS13, RPL8, RPS3, α-Tub, β-actin, RPL32, and elongation factor 1 alpha (EF1-α) were selected. Their expression levels were determined under four different experimental conditions (developmental stages, adult …

Workplace Aggression Against Healthcare Workers In A Spanish Healthcare Institution Between 2019 And 2021: The Impact Of The Covid-19 Pandemic, Aitor Díaz, Mireia Utzet, Joan Mirabent, Pilar Diaz, Jose Maria Ramada, Consol Serra, Fernando G Benavides

Faculty, Staff and Student Publications

OBJECTIVES: Describe the incidence of first aggressions among healthcare workers (HCWs) before and during the COVID-19 pandemic in a Spanish healthcare institution, according to workers' socio-occupational characteristics and analyze the impact of the pandemic on it.

METHODS: A cohort involving HCWs who worked in the institution for at least 1 week each year from 1 January 2019 to 31 December 2021. Adjusted relative risks (aRR) were estimated using generalized estimating equations and negative binomial models to calculate the differences in WPA between the different time periods. All analyses were stratified by gender.

RESULTS: Among women, the incidence was 6.8% (6.0; …

Plasma Enzymatic Activity, Proteomics And Peptidomics In Covid-19-Induced Sepsis: A Novel Approach For The Analysis Of Hemostasis, Fernando Dos Santos, Joyce B Li, Nathalia Juocys, Rafi Mazor, Laura Beretta, Nicole G Coufal, Michael T Y Lam, Mazen F Odish, Maria Claudia Irigoyen, Anthony J O'Donoghue, Federico Aletti, Erik B Kistler

Faculty, Staff and Student Publications

Introduction: Infection by SARS-CoV-2 and subsequent COVID-19 can cause viral sepsis. We investigated plasma protease activity patterns in COVID-19-induced sepsis with bacterial superinfection, as well as plasma proteomics and peptidomics in order to assess the possible implications of enhanced proteolysis on major protein systems (e.g., coagulation). Methods: Patients (=4) admitted to the intensive care units (ICUs) at the University of California, San Diego (UCSD) Medical Center with confirmed positive test for COVID-19 by real-time reverse transcription polymerase chain reaction (RT-PCR) were enrolled in a study approved by the UCSD Institutional Review Board (IRB# 190699, Protocol #20-0006). Informed consent was obtained …

Anti-Inflammatory Effects Of Vagus Nerve Stimulation In Pediatric Patients With Epilepsy, Supender Kaur, Nathan R Selden, Alejandro Aballay

Faculty, Staff and Student Publications

INTRODUCTION: The neural control of the immune system by the nervous system is critical to maintaining immune homeostasis, whose disruption may be an underlying cause of several diseases, including cancer, multiple sclerosis, rheumatoid arthritis, and Alzheimer's disease.

METHODS: Here we studied the role of vagus nerve stimulation (VNS) on gene expression in peripheral blood mononuclear cells (PBMCs). Vagus nerve stimulation is widely used as an alternative treatment for drug-resistant epilepsy. Thus, we studied the impact that VNS treatment has on PBMCs isolated from a cohort of existing patients with medically refractory epilepsy. A comparison of genome-wide changes in gene expression …

A Gcn-Based Approach To Uncover Misaligned Synonymous Terms In The Umls Metathesaurus, Xubing Hao, Rashmie Abeysinghe, Jay Shi, Licong Cui

Faculty, Staff and Student Publications

The Unified Medical Language System (UMLS), a large repository of biomedical vocabularies, has been used for supporting various biomedical applications. Ensuring the quality of the UMLS is critical to maintain both the accuracy of its content and the reliability of downstream applications. In this work, we present a Graph Convolutional Network (GCN)-based approach to identify misaligned synonymous terms organized under different UMLS concepts. We used synonymous terms grouped under the same concept as positive samples and top lexically similar terms as negative samples to train the GCN model. We applied the model to a test set and suggested those negative …

Gene Expression In Mice With Endothelium-Specific Telomerase Knockout, Zhanguo Gao, Yongmei Yu, Yulin Dai, Zhongming Zhao, Kristin Eckel-Mahan, Mikhail G Kolonin

Faculty, Staff and Student Publications

No abstract provided.

Investigating Cellular Heterogeneity At The Single-Cell Level By The Flexible And Mobile Extrachromosomal Circular Dna, Jiajinlong Kang, Yulin Dai, Jinze Li, Huihui Fan, Zhongming Zhao

Faculty, Staff and Student Publications

Extrachromosomal circular DNA (eccDNA) is a special class of DNA derived from linear chromosomes. It coexists independently with linear chromosomes in the nucleus. eccDNA has been identified in multiple organisms, including Homo sapiens, and has been shown to play important roles relevant to tumor progression and drug resistance. To date, computational tools developed for eccDNA detection are only applicable to bulk tissue. Investigating eccDNA at the single-cell level using a computational approach will elucidate the heterogeneous and cell-type-specific landscape of eccDNA within cellular context. Here, we performed the first eccDNA analysis at the single-cell level using data generated by single-cell …

Pediatric Traumatic Brain Injury In The Middle East And North Africa Region: A Systematic Review And Meta-Analysis To Assess Characteristics, Mechanisms, And Risk Factors, Samar Al-Hajj, Sarah H Farran, Batoul Dekmak, Layal Hneiny, Hussein Abou Abbas, Aya Hassoun, Nadine Youness, Sarah Ghalayini, Nour Abou Khalil, Fiona Lecky, Shima Shahjouieh, Layal Ghamlouche, Zainab Nasrallah, Firas Kobeissy

Faculty, Staff and Student Publications

Pediatric traumatic brain injury (pTBI) represents a major cause of child injuries in the Middle East and North Africa (MENA) region. This review aims to assess pTBIs in the MENA region and reports their clinical severity and outcomes. A search was conducted using major electronic databases, including Medline/Ovid, PubMed, EMBASE, Web of Science, and SCOPUS. Abstracts were screened independently and in duplicate to detect original research. The objective and study findings for each article were recorded, along with the mechanism of pTBI, patient age and sex, injury assessment tool(s) used, and outcome. A total of 1345 articles were retrieved, of …

Endothelial Activation And Fibrotic Changes Are Impeded By Laminar Flow-Induced Chk1-Senp2 Activity Through Mechanisms Distinct From Endothelial-To-Mesenchymal Cell Transition, Minh T H Nguyen, Masaki Imanishi, Shengyu Li, Khanh Chau, Priyanka Banerjee, Loka Reddy Velatooru, Kyung Ae Ko, Venkata S K Samanthapudi, Young J Gi, Ling-Ling Lee, Rei J Abe, Elena Mcbeath, Anita Deswal, Steven H Lin, Nicolas L Palaskas, Robert Dantzer, Keigi Fujiwara, Mae K Borchrdt, Estefani Berrios Turcios, Elizabeth A Olmsted-Davis, Sivareddy Kotla, John P Cooke, Guangyu Wang, Jun-Ichi Abe, Nhat-Tu Le

Faculty, Staff and Student Publications

BACKGROUND: The deSUMOylase sentrin-specific isopeptidase 2 (SENP2) plays a crucial role in atheroprotection. However, the phosphorylation of SENP2 at T368 under disturbed flow (D-flow) conditions hinders its nuclear function and promotes endothelial cell (EC) activation. SUMOylation has been implicated in D-flow-induced endothelial-to-mesenchymal transition (endoMT), but the precise role of SENP2 in counteracting this process remains unclear.

METHOD: We developed a phospho-specific SENP2 S344 antibody and generated knock-in (KI) mice with a phospho-site mutation of SENP2 S344A using CRISPR/Cas9 technology. We then investigated the effects of SENP2 S344 phosphorylation under two distinct flow patterns and during hypercholesteremia (HC)-mediated EC activation.

RESULT: …

Digital Solutions Observed In Clinical Trials: A Formative Feasibility Scoping Review, Taylor M Harrison, Sungrim Moon, Liwei Wang, Sunyang Fu, Hongfang Liu

Faculty, Staff and Student Publications

Growing digital access accelerates digital transformation of clinical trials where digital solutions (DSs) are increasingly and widely leveraged for improving trial efficiency, effectiveness, and accessibility. Many factors impact DS success including technology barriers, privacy concerns, or user engagement activities. It is unclear how those factors are considered or reported in the literature. Here, we perform a formative feasibility scoping review to identify gaps impacting DS quality and reproducibility in trials. Articles containing digital terms published in English from 2009 to 2022 were collected (n=4,167). 130 articles published between 2016 and 2022 were randomly selected for full-text review. Eligible articles (n=100) …

Contextual Variation Of Clinical Notes Induced By Ehr Migration, Kurt Miller, Sungrim Moon, Sunyang Fu, Hongfang Liu

Faculty, Staff and Student Publications

The structure and semantics of clinical notes vary considerably across different Electronic Health Record (EHR) systems, sites, and institutions. Such heterogeneity hampers the portability of natural language processing (NLP) models in extracting information from the text for clinical research or practice. In this study, we evaluate the contextual variation of clinical notes by measuring the semantic and syntactic similarity of the notes of two sets of physicians comprising four medical specialties across EHR migrations at two Mayo Clinic sites. We find significant semantic and syntactic variation imposed by the context of the EHR system and between medical specialties whereas only …

Oncology-Specific Radiation Dose And Image Noise Reference Levels In Adult Abdominal-Pelvic Ct, Moiz Ahmad, Xinming Liu, Ajaykumar C Morani, Dhakshinamoorthy Ganeshan, Marcus R Anderson, Ehsan Samei, Corey T Jensen

Faculty, Staff and Student Publications

OBJECTIVES: To provide our oncology-specific adult abdominal-pelvic CT reference levels for image noise and radiation dose from a high-volume, oncologic, tertiary referral center.

METHODS: The portal venous phase abdomen-pelvis acquisition was assessed for image noise and radiation dose in 13,320 contrast-enhanced CT examinations. Patient size (effective diameter) and radiation dose (CTDI

RESULTS: The noise reference level was 11.25 HU with a reference range of 10.25-12.25 HU. The dose reference level at a median effective diameter of 30.7 cm was 26.7 mGy with a reference range of 19.6-37.0 mGy. Dose increased with patient size; however, image noise remained approximately constant within …