Biomedical Informatics Commons^™

Surgical Management Of Brain Metastasis: Challenges And Nuances, Chibawanye I Ene, Sherise D Ferguson

Faculty, Staff and Student Publications

Brain metastasis is the most common type of intracranial tumor. The contemporary management of brain metastasis is a challenging issue and traditionally has carried a poor prognosis as these lesions typically occur in the setting of advanced cancer. However, improvement in systemic therapy, advances in radiation techniques and multimodal therapy tailored to the individual patient, has given hope to this patient population. Surgical resection has a well-established role in the management of brain metastasis. Here we discuss the evolving role of surgery in the treatment of this diverse patient population.

Residual Cancer Burden After Neoadjuvant Chemotherapy And Long-Term Survival Outcomes In Breast Cancer: A Multicentre Pooled Analysis Of 5161 Patients, Christina Yau, Marie Osdoit, Marieke Van Der Noordaa, Sonal Shad, Jane Wei, Diane De Croze, Anne-Sophie Hamy, Marick Laé, Fabien Reyal, Gabe S Sonke, Tessa G Steenbruggen, Maartje Van Seijen, Jelle Wesseling, Miguel Martín, Maria Del Monte-Millán, Sara López-Tarruella, Judy C Boughey, Matthew P Goetz, Tanya Hoskin, Rebekah Gould, Vicente Valero, Stephen B Edge, Jean E Abraham, John M S Bartlett, Carlos Caldas, Janet Dunn, Helena Earl, Larry Hayward, Louise Hiller, Elena Provenzano, Stephen-John Sammut, Jeremy S Thomas, David Cameron, Ashley Graham, Peter Hall, Lorna Mackintosh, Fang Fan, Andrew K Godwin, Kelsey Schwensen, Priyanka Sharma, Angela M Demichele, Kimberly Cole, Lajos Pusztai, Mi-Ok Kim, Laura J Van 'T Veer, Laura J Esserman, W Fraser Symmans

Faculty, Staff and Student Publications

Background: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings.

Methods: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, …

Association Of Proton Pump Inhibitor Use With Survival Outcomes In Cancer Patients Treated With Immune Checkpoint Inhibitors: A Systematic Review And Meta-Analysis, Baoqing Chen, Chen Yang, Mihnea P Dragomir, Dongmei Chi, Wenyan Chen, David Horst, George A Calin, Qiaoqiao Li

Faculty, Staff and Student Publications

Background: Proton pump inhibitors (PPIs) have been shown to regulate the gut microbiome and affect the response to immune checkpoint inhibitors (ICIs). Contradictory results on survival have been observed in patients concomitantly treated with ICIs and PPIs. We performed a systematic review and meta-analysis to determine the association between PPI use and survival outcomes in ICI-treated cancer patients.

Methods: EMBASE, MEDLINE/PubMed, Cochrane Library databases, and major oncology conference proceedings were searched. Studies comparing overall survival (OS) and progression-free survival (PFS) between PPI-treated and PPI-free groups of ICI-treated cancer patients were included. Data regarding study and patient characteristics, ICI and PPI …

The Seen And The Unseen: Molecular Classification And Image Based-Analysis Of Gastrointestinal Cancers, Corina-Elena Minciuna, Mihai Tanase, Teodora Ecaterina Manuc, Stefan Tudor, Vlad Herlea, Mihnea P Dragomir, George A Calin, Catalin Vasilescu

Faculty, Staff and Student Publications

Gastrointestinal cancers account for 22.5% of cancer related deaths worldwide and represent circa 20% of all cancers. In the last decades, we have witnessed a shift from histology-based to molecular-based classifications using genomic, epigenomic, and transcriptomic data. The molecular based classification revealed new prognostic markers and may aid the therapy selection. Because of the high-costs to perform a molecular classification, in recent years immunohistochemistry-based surrogate classification were developed which permit the stratification of patients, and in parallel multiple groups developed hematoxylin and eosin whole slide image analysis for sub-classifying these entities. Hence, we are witnessing a return to an image-based …

Translating Mentoring Interventions Research Into Practice: Evaluation Of An Evidence-Based Workshop For Research Mentors On Developing Trainees’ Scientific Communication Skills, Erin K Dahlstrom, Christine Bell, Shine Chang, Hwa Young Lee, Cheryl B Anderson, Annie Pham, Christine Maidl Pribbenow, Carrie A Cameron

Faculty, Staff and Student Publications

A key part of keeping doctoral and postdoctoral trainees in STEM research careers is mentoring. Our previous research indicates that mentoring trainees in scientific communication (SC) skill development increases research career intention through two social-cognitive constructs, self-efficacy in and outcome expectations for acquiring SC skills, as well as science identity. While many mentor training interventions exist, no programs focus on developing SC skills specifically. The "Scientific Communication Advances Research Excellence" (SCOARE) program trains mentors to address trainee scientific communication (SC) skill development as an innovative approach to increase trainee research career persistence. The SCOARE training is a half-day workshop for …

A Narrative Review On Invasive Brain Stimulation For Treatment-Resistant Depression, Manoj P Dandekar, Alexandre P Diaz, Ziaur Rahman, Ritele H Silva, Ziad Nahas, Scott Aaronson, Sudhakar Selvaraj, Albert J Fenoy, Marsal Sanches, Jair C Soares, Patricio Riva-Posse, Joao Quevedo

Faculty, Staff and Student Publications

While most patients with depression respond to pharmacotherapy and psychotherapy, about one-third will present treatment resistance to these interventions. For patients with treatment-resistant depression (TRD), invasive neurostimulation therapies such as vagus nerve stimulation, deep brain stimulation, and epidural cortical stimulation may be considered. We performed a narrative review of the published literature to identify papers discussing clinical studies with invasive neurostimulation therapies for TRD. After a database search and title and abstract screening, relevant English-language articles were analyzed. Vagus nerve stimulation, approved by the U.S. Food and Drug Administration as a TRD treatment, may take several months to show therapeutic …

Serum Gamma Glutamyltransferase (Ggt) In Coronary Artery Disease: Exploring The Asian Indian Connection, Kunal K Singh, Aditya Kapoor, Roopali Khanna, Ankit Sahu, Vishwas Kapoor, Sudeep Kumar, Naveen Garg, Satyendra Tewari, Pravin Goel

Faculty, Staff and Student Publications

BACKGROUND: There is a need to identify novel markers for CAD, independent of traditional CV risk factors. One of these is gamma-glutamyl transferase (GGT), a marker of increased oxidative stress. Given the high prevalence of CAD in Asian Indians, the link of GGT and CAD in them needs to be studied.

AIM: To assess GGT in patients with angiographically documented CAD.

METHODS AND RESULTS: Two hundred patients aged 58.1 ± 9.95 years, 73% males, hypertension 56%, diabetes 40% were included. Mean GGT was 63.6 ± 44.33 (10–269 U/L). The levels of GGT progressively increased in those with single/double or triple-vessel …

Defective Dna Polymerase Beta Invoke A Cytosolic Dna Mediated Inflammatory Response, Shengyuan Zhao, Julia A Goewey Ruiz, Manu Sebastian, Dawit Kidane

Faculty, Staff and Student Publications

Base excision repair (BER) has evolved to maintain the genomic integrity of DNA following endogenous and exogenous agent induced DNA base damage. In contrast, aberrant BER induces genomic instability, promotes malignant transformation and can even trigger cancer development. Previously, we have shown that deoxyribo-5'-phosphate (dRP) lyase deficient DNA polymerase beta (POLB) causes replication associated genomic instability and sensitivity to both endogenous and exogenous DNA damaging agents. Specifically, it has been established that this loss of dRP lyase function promotes inflammation associated gastric cancer. However, the way that aberrant POLB impacts the immune signaling and inflammatory responses is still unknown. Here …

Evaluating A Pilot Culturally Sensitive Psychosocial Intervention On Posttraumatic Growth For Chinese American Breast Cancer Survivors, Qiao Chu, Moni Tang, Lingjun Chen, Lucy Young, Alice Loh, Carol Wang, Qian Lu

Faculty, Staff and Student Publications

This study investigated the potential benefit of a pilot culturally sensitive group support intervention, named Joy Luck Academy (JLA), in fostering posttraumatic growth among Chinese American breast cancer survivors. Eighty-six Chinese American breast cancer survivors participated in an eight-week single-arm pre-/post-test trial of an intervention program, which included educational lectures and peer mentor support. The JLA participants were compared with an independent sample of 109 Chinese American breast cancer survivors who went through routine care. Both groups completed baseline and eight-week follow-up assessments of the five facets of posttraumatic growth (meaningful interpersonal relationships, finding new possibilities in life, personal strength, …

Quaking But Not Parkin Is The Major Tumor Suppressor In 6q Deleted Region In Glioblastoma, Fatma Betul Aksoy Yasar, Takashi Shingu, Daniel B Zamler, Mohammad Fayyad Zaman, Derek Lin Chien, Qiang Zhang, Jiangong Ren, Jian Hu

Faculty, Staff and Student Publications

Glioblastoma (GBM) is a high-grade, aggressive brain tumor with dismal median survival time of 15 months. Chromosome 6q (Ch6q) is a hotspot of genomic alterations, which is commonly deleted or hyper-methylated in GBM. Two neighboring genes in this region, QKI and PRKN have been appointed as tumor suppressors in GBM. While a genetically modified mouse model (GEMM) of GBM has been successfully generated with Qk deletion in the central nervous system (CNS), in vivo genetic evidence supporting the tumor suppressor function of Prkn has not been established. In the present study, we generated a mouse model with Prkn-null allele …

Update On Mri In Evaluation And Treatment Of Endometrial Cancer, Ekta Maheshwari, Stephanie Nougaret, Erica B Stein, Gaiane M Rauch, Ken-Pin Hwang, R Jason Stafford, Ann H Klopp, Pamela T Soliman, Katherine E Maturen, Andrea G Rockall, Susanna I Lee, Elizabeth A Sadowski, Aradhana M Venkatesan

Faculty, Staff and Student Publications

Endometrial cancer is the second most common gynecologic cancer worldwide and the most common gynecologic cancer in the United States, with an increasing incidence in high-income countries. Although the International Federation of Gynecology and Obstetrics (FIGO) staging system for endometrial cancer is a surgical staging system, contemporary published evidence-based data and expert opinions recommend MRI for treatment planning as it provides critical diagnostic information on tumor size and depth, extent of myometrial and cervical invasion, extrauterine extent, and lymph node status, all of which are essential in choosing the most appropriate therapy. Multiparametric MRI using a combination of T2-weighted sequences, …

Modeling Recurrence In Idiopathic Subglottic Stenosis With Mobile Peak Expiratory Flow, Kyle Kimura, Liping Du, Lynn D Berry, Li-Ching Huang, Sheau-Chiann Chen, David O Francis, Alexander Gelbard

Faculty, Staff and Student Publications

OBJECTIVES/HYPOTHESIS: We sought to establish normative peak expiratory flow (PEF) data for patients with idiopathic subglottic stenosis (iSGS), evaluate whether immediate changes in PEF after a procedure predict long-term treatment response, and test if a decline in longitudinal PEF is associated with disease recurrence.

STUDY DESIGN: International, prospective, 3-year multicenter cohort study of 810 patients with untreated, newly diagnosed, or previously treated iSGS.

METHODS: iSGS patients consented and enrolled in the North American Airway Collaborative (NoAAC) iSGS

RESULTS: Within the NoAAC iSGS1000 cohort, 810 patients participated in a 3-year, prospective study comparing surgical treatment efficacy and 385 had appropriate PEF …

Nrf1 Association With Auts2-Polycomb Mediates Specific Gene Activation In The Brain, Sanxiong Liu, Kimberly A Aldinger, Chi Vicky Cheng, Takae Kiyama, Mitali Dave, Hanna K Mcnamara, Wukui Zhao, James M Stafford, Nicolas Descostes, Pedro Lee, Stefano G Caraffi, Ivan Ivanovski, Edoardo Errichiello, Christiane Zweier, Orsetta Zuffardi, Michael Schneider, Antigone S Papavasiliou, M Scott Perry, Jennifer Humberson, Megan T Cho, Astrid Weber, Andrew Swale, Tudor C Badea, Chai-An Mao, Livia Garavelli, William B Dobyns, Danny Reinberg

Faculty, Staff and Student Publications

The heterogeneous family of complexes comprising Polycomb repressive complex 1 (PRC1) is instrumental for establishing facultative heterochromatin that is repressive to transcription. However, two PRC1 species, ncPRC1.3 and ncPRC1.5, are known to comprise novel components, AUTS2, P300, and CK2, that convert this repressive function to that of transcription activation. Here, we report that individuals harboring mutations in the HX repeat domain of AUTS2 exhibit defects in AUTS2 and P300 interaction as well as a developmental disorder reflective of Rubinstein-Taybi syndrome, which is mainly associated with a heterozygous pathogenic variant in CREBBP/EP300. Moreover, the absence of AUTS2 or mutation in its …

Comprehensive Characterization Of Covid-19 Patients With Repeatedly Positive Sars-Cov-2 Tests Using A Large Us Electronic Health Record Database, Xiao Dong, Yujia Zhou, Xiao-Ou Shu, Elmer V Bernstam, Rebecca Stern, David M Aronoff, Hua Xu, Loren Lipworth

Faculty, Staff and Student Publications

In the absence of genome sequencing, two positive molecular tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) separated by negative tests, prolonged time, and symptom resolution remain the best surrogate measure of possible reinfection. Using a large electronic health record database, we characterized clinical and testing data for 23 patients with repeatedly positive SARS-CoV-2 PCR test results ≥60 days apart, separated by ≥2 consecutive negative test results. The prevalence of chronic medical conditions, symptoms, and severe outcomes related to coronavirus disease 19 (COVID-19) illness were ascertained. The median age of patients was 64.5 years, 40% were Black, and 39% …

A Comparison Of Machine Learning Classifiers For Pediatric Epilepsy Using Resting-State Functional Mri Latency Data, Ryan D Nguyen, Matthew D Smyth, Liang Zhu, Ludovic P Pao, Shannon K Swisher, Emmett H Kennady, Anish Mitra, Rajan P Patel, Jeremy E Lankford, Gretchen Von Allmen, Michael W Watkins, Michael E Funke, Manish N Shah

Faculty, Staff and Student Publications

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from …

First-In-Human Segmental Esophageal Reconstruction Using A Bioengineered Mesenchymal Stromal Cell-Seeded Implant, Johnathon M Aho, Saverio La Francesca, Scott D Olson, Fabio Triolo, Jeff Bouchard, Laura Mondano, Sumati Sundaram, Christina Roffidal, Charles S Cox, Louis M Wong Kee Song, Sameh M Said, William Fodor, Dennis A Wigle

Faculty, Staff and Student Publications

INTRODUCTION: Resection and reconstruction of the esophagus remains fraught with morbidity and mortality. Recently, data from a porcine reconstruction model revealed that segmental esophageal reconstruction using an autologous mesenchymal stromal cell-seeded polyurethane graft (Cellspan esophageal implant [CEI]) can facilitate esophageal regrowth and regeneration. To this end, a patient requiring a full circumferential esophageal segmental reconstruction after a complex multiorgan tumor resection was approved for an investigational treatment under the Food and Drug Administration Expanded Access Use (Investigational New Drug 17402).

METHODS: Autologous adipose-derived mesenchymal stromal cells (Ad-MSCs) were isolated from the Emergency Investigational New Drug patient approximately 4 weeks before …

Digital Technology Needs In Maternal Mental Health: A Qualitative Inquiry, Alexandra Zingg, Laura Carter, Deevakar Rogith, Amy Franklin, Sudhakar Selvaraj, Jerrie Refuerzo, Sahiti Myneni

Faculty, Staff and Student Publications

Digital technologies offer many opportunities to improve mental healthcare management for women seeking pre- and-postnatal care. They provide a discrete, practical medium that is well-suited for the sensitive nature of mental health. Women who are more prone to experiencing peripartum depression (PPD), such as those of low-socioeconomic background or in high-risk pregnancies, can benefit the most from such technologies. However, current digital interventions directed towards this population provide suboptimal support, and their responsiveness to end user needs is quite limited. Our objective is to understand the digital terrain of information needs for low-socioeconomic status women with high-risk pregnancies, specifically within …

Med-Bert: Pretrained Contextualized Embeddings On Large-Scale Structured Electronic Health Records For Disease Prediction, Laila Rasmy, Yang Xiang, Ziqian Xie, Cui Tao, Degui Zhi

Faculty, Staff and Student Publications

Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver impressive performance in many clinical tasks. Large training cohorts, however, are often required by these models to achieve high accuracy, hindering the adoption of DL-based models in scenarios with limited training data. Recently, bidirectional encoder representations from transformers (BERT) and related models have achieved tremendous successes in the natural language processing domain. The pretraining of BERT on a very large training corpus generates contextualized embeddings that can boost the performance of models trained on smaller datasets. Inspired by BERT, we propose Med-BERT, which adapts the BERT framework originally developed …

Generalized And Transferable Patient Language Representation For Phenotyping With Limited Data, Yuqi Si, Elmer V Bernstam, Kirk Roberts

Faculty, Staff and Student Publications

The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task pre-training and fine-tuning approach for learning generalized and transferable patient representations from medical language. The model is first pre-trained with different but related high-prevalence phenotypes and further fine-tuned on downstream target tasks. Our main contribution focuses on the impact this technique can have on low-prevalence phenotypes, a challenging task due to the dearth of data. We validate the representation from pre-training, and fine-tune the multi-task pre-trained models on low-prevalence phenotypes including 38 circulatory diseases, 23 …

Exchanges In A Virtual Environment For Diabetes Self-Management Education And Support: Social Network Analysis, Carlos A Pérez-Aldana, Allison A Lewinski, Constance M Johnson, Allison A Vorderstrasse, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Diabetes remains a major health problem in the United States, affecting an estimated 10.5% of the population. Diabetes self-management interventions improve diabetes knowledge, self-management behaviors, and clinical outcomes. Widespread internet connectivity facilitates the use of eHealth interventions, which positively impacts knowledge, social support, and clinical and behavioral outcomes. In particular, diabetes interventions based on virtual environments have the potential to improve diabetes self-efficacy and support, while being highly feasible and usable. However, little is known about the patterns of social interactions and support taking place within type 2 diabetes-specific virtual communities.

OBJECTIVE: The objective of this study was to …

A Comparison Of Exhaustive And Non-Lattice-Based Methods For Auditing Hierarchical Relations In Gene Ontology, Rashmie Abeysinghe, Fengbo Zheng, Licong Cui

Faculty, Staff and Student Publications

Uncovering and fixing errors in biomedical terminologies is essential so that they provide accurate knowledge to downstream applications that rely on them. Non-lattice-based methods have been applied to identify various kinds of inconsistencies in different biomedical terminologies. In previous work, we have introduced two inference-based approaches that were applied in an exhaustive manner to audit hierarchical relations in the Gene Ontology: (1) Lexical-based inference framework, and (2) Subsumption-based sub-term inference framework. However, it is unclear how effective these exhaustive approaches perform compared with their corresponding non-lattice-based approaches. Therefore, in this paper, we implement the non-lattice versions of these two exhaustive …

Towards Digestible Digital Health Solutions: Application Of A Health Literacy Inclusive Development Framework For Peripartum Depression Management, Alexandra Zingg, Tavleen Singh, Sahiti Myneni

Faculty, Staff and Student Publications

Women of low income and education have lower levels of peripartum depression (PPD) literacy, limiting their ability to recognize symptoms and make informed healthcare decisions. Existing digital solutions and underlying development frameworks for PPD lack an integrative approach addressing health literacy and related disparities. Therefore, we develop an integrative framework for digital content engineering in PPD self-management consisting of (a) user needs analysis, (b) inclusion of eHealth literacy principles (science and health literacy), and (c) mapping user needs to the Behavioral Intervention Technology model. Results revealed that perinatal women seeking mental health care prefer information in multisensory formats, and knowledge …

Cross-Vendor Ct Image Data Harmonization Using Cvh-Ct, Md Selim, Jie Zhang, Baowei Fei, Guo-Qiang Zhang, Gary Yeeming Ge, Jin Chen

Faculty, Staff and Student Publications

While remarkable advances have been made in Computed Tomography (CT), most of the existing efforts focus on imaging enhancement while reducing radiation dose. How to harmonize CT image data captured using different scanners is vital in cross-center large-scale radiomics studies but remains the boundary to explore. Furthermore, the lack of paired training image problem makes it computationally challenging to adopt existing deep learning models. We propose a novel deep learning approach called CVH-CT for harmonizing CT images captured using scanners from different vendors. The generator of CVH-CT uses a self-attention mechanism to learn the scanner-related information. We also propose a …

Identifying Sleep-Related Factors Associated With Cognitive Function In A Hispanics/Latinos Cohort: A Dual Random Forest Approach, Li Xiaojin, Cui Licong, Wang Fei, Paul E Schulz, Guo-Qiang Zhang

Faculty, Staff and Student Publications

Disordered sleep is associated with poor cognitive function and cognitive decline. However, little is known regarding the association of sleep-related factors with cognitive function in underrepresented cohorts such as the Hispanic/Latino population. Leveraging the National Sleep Research Resource, one of the most comprehensive collections of sleep studies, we identified a Hispanic/Latino cohort of 1,031 lower cognitive function cases and 2,062 normal controls. We developed a novel dual random forest (DRF) approach to discriminate cases against controls for estimating the potential impact of sleep-related variables related to the decline of cognitive function. Several important sleep-related factors were identified which may be …

Carving The Path To Allogeneic Car T Cell Therapy In Acute Myeloid Leukemia, Oren Pasvolsky, May Daher, Gheath Alatrash, David Marin, Naval Daver, Farhad Ravandi, Katy Rezvani, Elizabeth Shpall, Partow Kebriaei

Faculty, Staff and Student Publications

Despite advances in the understanding of the genetic landscape of acute myeloid leukemia (AML) and the addition of targeted biological and epigenetic therapies to the available armamentarium, achieving long-term disease-free survival remains an unmet need. Building on growing knowledge of the interactions between leukemic cells and their bone marrow microenvironment, strategies to battle AML by immunotherapy are under investigation. In the current review we describe the advances in immunotherapy for AML, with a focus on chimeric antigen receptor (CAR) T cell therapy. CARs constitute powerful immunologic modalities, with proven clinical success in B-Cell malignancies. We discuss the challenges and possible …

Deep Learning For Automated Analysis Of Cellular And Extracellular Components Of The Foreign Body Response In Multiphoton Microscopy Images, Mattia Sarti, Maria Parlani, Luis Diaz-Gomez, Antonios G Mikos, Pietro Cerveri, Stefano Casarin, Eleonora Dondossola

Faculty, Staff and Student Publications

The Foreign body response (FBR) is a major unresolved challenge that compromises medical implant integration and function by inflammation and fibrotic encapsulation. Mice implanted with polymeric scaffolds coupled to intravital non-linear multiphoton microscopy acquisition enable multiparametric, longitudinal investigation of the FBR evolution and interference strategies. However, follow-up analyses based on visual localization and manual segmentation are extremely time-consuming, subject to human error, and do not allow for automated parameter extraction. We developed an integrated computational pipeline based on an innovative and versatile variant of the U-Net neural network to segment and quantify cellular and extracellular structures of interest, which is …

Security And Privacy When Applying Fair Principles To Genomic Information, Jaime Delgado, Silvia Llorente

Faculty, Staff and Student Publications

Making data Findable, Accessible, Interoperable and Reusable (FAIR) is a good approach when data needs to be shared. However, security and privacy are still critical aspects. In the FAIRification process, there is a need both for de-identification of data and for license attribution. The paper analyses some of the issues related to this process when the objective is sharing genomic information. The main results are the identification of the already existing standards that could be used for this purpose and how to combine them. Nevertheless, the area is quickly evolving and more specific standards could be specified.

Representation Of Ehr Data For Predictive Modeling: A Comparison Between Umls And Other Terminologies, Laila Rasmy, Firat Tiryaki, Yujia Zhou, Yang Xiang, Cui Tao, Hua Xu, Degui Zhi

Faculty, Staff and Student Publications

OBJECTIVE: Predictive disease modeling using electronic health record data is a growing field. Although clinical data in their raw form can be used directly for predictive modeling, it is a common practice to map data to standard terminologies to facilitate data aggregation and reuse. There is, however, a lack of systematic investigation of how different representations could affect the performance of predictive models, especially in the context of machine learning and deep learning.

MATERIALS AND METHODS: We projected the input diagnoses data in the Cerner HealthFacts database to Unified Medical Language System (UMLS) and 5 other terminologies, including CCS, CCSR, …

Understanding Spatial Language In Radiology: Representation Framework, Annotation, And Spatial Relation Extraction From Chest X-Ray Reports Using Deep Learning, Surabhi Datta, Yuqi Si, Laritza Rodriguez, Sonya E Shooshan, Dina Demner-Fushman, Kirk Roberts

Faculty, Staff and Student Publications

Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Such spatial relationships are also linked to various differential diagnoses and often described through uncertainty phrases. Structured representation of this clinically significant spatial information has the potential to be used in a variety of downstream clinical informatics applications. Our focus is to extract these spatial representations from the reports. For this, we first define a representation framework based on the Spatial Role Labeling (SpRL) scheme, which we refer to as …

Critical Micrornas And Regulatory Motifs In Cleft Palate Identified By A Conserved Mirna-Tf-Gene Network Approach In Humans And Mice, Aimin Li, Peilin Jia, Saurav Mallik, Rong Fei, Hiroki Yoshioka, Akiko Suzuki, Junichi Iwata, Zhongming Zhao

Faculty, Staff and Student Publications

Cleft palate (CP) is the second most common congenital birth defect. The etiology of CP is complicated, with involvement of various genetic and environmental factors. To investigate the gene regulatory mechanisms, we designed a powerful regulatory analytical approach to identify the conserved regulatory networks in humans and mice, from which we identified critical microRNAs (miRNAs), target genes and regulatory motifs (miRNA-TF-gene) related to CP. Using our manually curated genes and miRNAs with evidence in CP in humans and mice, we constructed miRNA and transcription factor (TF) co-regulation networks for both humans and mice. A consensus regulatory loop (miR17/miR20a-FOXE1-PDGFRA) and eight …