News and Events

 

Chair’s Message

pth-use-this-oneWe are moving toward our vision with a number of activities across our various programs. We have updated our strategic plan in response to the 10-year academic program review that we recently completed. For our research-oriented MS and PhD programs, we have recently added a specialization in Data Science. We are completing a curriculum revision for our on line applied clinical informatics MS which will be effective Fall 2020. The work of our fellows in the clinical informatics fellowship program has received plaudits from clinical administrators and faculty, and we are currently recruiting a new faculty member in our department to assist with this program (view position description).  We are also recruiting a faculty member in medical education to start Summer 2020 (view position description). This is the beginning of a new cycle of admissions to our graduate programs, and we look forward to another productive year, and new growth in our department.

Cordially,

Peter Tarczy-Hornoch, MD
Chair and Professor, Department of Biomedical Informatics and Medical Education

Biomedical Informatics and Medical Education Newsletter

 

June 6 – 10, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: See you all next Fall!

PUBLICATIONS & PRESENTATIONS
  1. Dong, X. Zhang, G. Luo. Improving the Accuracy of Progress Indication for Constructing Deep Learning Models. IEEE Access, 2022.

Nic Dobbins, Tony Mullen, Ozlem Uzuner and Meliha Yetisgen (accepted). The Leaf Clinical Trials Corpus: A new resource for query generation from clinical trial eligibility criteria. Nature Scientific Data.

ANNOUNCEMENTS

Congratulations! Starmerx International Inc. provided Prof. Gang Luo a research gift of $30K to support his computer science research work.

May 30 – June 3, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: See you all next Fall!

PUBLICATIONS & PRESENTATIONS

Walter H. Curioso, Ph.D., M.D., M.P.H., Affiliate Associate Professor in Biomedical Informatics and Medical Education, has been profiled in the last issue of Nature Communications as digital health expert researcher with experience in planning and deployment of digital medicine tools in under-resourced settings. RELATED PUBLICATION: Challenges in digital medicine applications in under-resourced settings. Nature Communications 13, 3020 (2022). https://doi.org/10.1038/s41467-022-30728-3

Hannah A. Burkhardt, Michael D. Pullmann, Thomas D. Hull, Patricia A. Areán and Trevor Cohen. Comparing emotion feature extraction approaches for predicting depression and anxiety. Accepted – CLPsych2022

Kevin Lybarger, Justin Tauscher, Xiruo Ding, Dror Ben-Zeev and Trevor Cohen. Identifying Distorted Thinking in Patient-Therapist Text Message Exchanges by Leveraging Dynamic Multi-Turn Context. Accepted – CLPsych2022

UPCOMING GENERAL EXAM

Reggie Casanova-Perez

Date: June 8th, 2022

Time: 1:00 pm – 2:00 pm

Zoom: https://washington.zoom.us/j/96468688124?pwd=ck9ML2k3Qk9Wa2VTTUJiWWZBTkU1Zz09

Title: Queering the EHR: Uncovering the embedded cisheteronormativity in Health Information Technologies

Abstract: Transgender and Gender Diverse (TGD) people have been historically stigmatized and victims of structural discrimination because their identities, bodies, and social expressions are disruptive to social norms. The growing TGD community in the US, especially among adults, has experienced significant health inequities that compromise the health care they receive. These inequities have grown with the advancement of health information technology (HIT). These technologies, such as the Electronic Health Records or Clinical Decision Support Systems, have unfortunately been conditioned by and established with cisheteronormativity concepts (i.e., the assumption that everyone is cisgender – a person whose gender identity matches with the one assigned at birth – and heterosexual). This conditioning has created a healthcare environment that is not inclusive, welcoming, or affirming to TGD patients as the workflow is not fit for validating and meeting the needs of TGD patients. By combining two theoretical frameworks, (1) the Gender Minority Stress and Resilience model and (2) the Socio-technical model for Health Information Technology, I aim to explore the extent to which cisheteronormativity is embedded in HIT. I will accomplish this by first identifying challenges associated with HIT and cisheteronormativity through a literature review (Aim 1). Then, I will qualitatively interview healthcare providers (Aim 2) and TGD patients (Aim 3) to identify pain points in TGD care and opportunities for improvement in their clinical routine. Based on the outcome of these three aims, I will generate HIT design recommendations for creating a more welcoming and inclusive healthcare environment for TGD patients to ensure that their healthcare needs are met without invalidating their identity. This novel set of recommendations can have a revolutionary role in addressing TGD health inequities as it will actively confront the influence that cisheteronormativity has on HIT and highlight methods that deliver affirmatory and inclusive care that meets the healthcare needs of TGD patients.

UPCOMING FINAL EXAM

Harsh Patel

Date: June 8th, 2022

Time: 12:00 pm – 1:00 pm

Zoom: https://washington.zoom.us/j/7233069904?pwd=QXk3WDc4dW9iYVZ4dHEvN3p6VmpoQT09

Title: Using user-centered design to unburden genetic analyses for novice genomics researchers

Abstract: Increasingly larger genomic databases have allowed for more robust genetic analyses, leading to advances in bioinformatics, translational medicine, and, ultimately, improving patient care. One of the backbones behind these advancements are the plethora of bioinformatics tools available to researchers that allow for more efficient and accurate experiments. However, there exist major design gaps and usability flaws in most of these instruments, which lead to user frustration, time delay of obtaining novel results or re-running existing queries with different parameters, and the lack of compatibility with other tools. One proposed solution to these challenges proposes the usage of user-centered design (UCD) principles during the design, development, and evaluation of new bioinformatics tools. In the proposed study, we aim to develop a user-friendly, cloud-based genomics analysis tool

that will better allow novice genomics researchers to run analyses in order to ultimately improve patient care. We will begin by conducting a literature review on existing, commonly-used genomics tools in order to derive a framework for the usability evaluation of such tools. Furthermore, we will conduct an assessment on the existing challenges and needs of novice genomics researchers (Aim 1). Thereafter, UCD principles will be utilized with the knowledge gained from Aim 1 to create a user-friendly, cloud-agnostic genomics analysis tool that will allow the target users to more easily perform genetic experiments (Aim 2). Finally, we will utilize the evaluation framework developed in Aim 1 to evaluate the analysis tool developed in Aim 2 and develop a set of guidelines and recommendations for implementation (Aim 3). By doing so, we aim to unburden the tasks of hypothesis generation, variant discovery, and risk assessment in both existing and novel healthcare settings.

ANNOUNCEMENTS

New grant from the National Library of Medicine:

R01 LM0104056.

Cohen and Pakhomov (MPI). Yetisgen (Co-I).

Title: DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP.

Project Period: 06/01/2022 – 02/28/2026

Deep neural transformer networks have advanced Natural Language Processing (NLP) performance, but are large models with many parameters, and hence vulnerable to bias. The large data sets required to train these models may be drawn from different study sites or clinical units, leading to confounding by provenance where models make predictions using the characteristics of these data sources instead of diagnostically relevant information, with erroneous predictions at the point of deployment. Our project aims to develop validated approaches for Deconfounding Deep Transformer Networks (DeconDTN) and disseminate them as open source tools so that these powerful models can be applied more reliably to clinical problems.

Please join me in welcoming Frances Wedge to the department as our new part-time Fiscal Specialist. Frances comes to us from UW Medical Center and is excited to put her Associate’s Degree in Accounting to use. Frances will be working Monday through Friday from 10:00 am to 2:00 pm.

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

May 23 – 27, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, June 2nd at 11:00 am

Presenters: Gang Luo, Professor, Biomedical Informatics and Medical Education and Qifei Dong, BHI PhD Student

Title: Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs Using an Adaptation of the Genant Semiquantitative Criteria

Via Zoom: https://washington.zoom.us/my/peter.th

PUBLICATIONS & PRESENTATIONS

“Sharing inpatient clinical notes with patients and caregivers:  Too early or long overdue?”  Panel presentation: Thomas Payne,  S. Trent Rosenbloom, David K. Vawdrey, and Michelle M. Kelly.  AMIA Clinical Informatics Conference, Houston, TX, May 24, 2022.

UPCOMING FINAL EXAM

Aakash Sur

Date: June 3, 2022

Time: 11:00 am – 12:30 pm

Zoom Link:  https://washington.zoom.us/j/93008828511

Title: Data Driven Methods for Scaffolding Genomes with Hi-C

Abstract: High-quality reference genomes are once again in vogue with the publication of the telomere-to-telomere human genome and several challenging plant and animal genomes. Latest efforts around genome assembly have coalesced around two key technologies – ultra long reads and genome chromatin conformation capture (Hi-C). Here, we used both to complete the protist genomes of L. donovani, L. tarentolae, C. fasciculata, and E. gracilis, shedding light on their genomic organization and evolutionary history. To navigate the many Hi-C genome scaffolding methods, we benchmarked the most popular methods against a set of high-quality reference genomes. We found that while most can operate well under ideal circumstances, many struggle with using modern high-quality assemblies which contain near chromosome length contigs. Finally, we attempted to overcome these limitations using a machine learning approach by leveraging the recent bounty of genomes that have been published with Hi-C. Using an innovative convolutional neural network, we demonstrated a proof of concept for a data driven approach to scaffolding genomes.

ANNOUNCEMENTS

Serena Xie, and Andrea Hartzler (PI) , along with Drs. Patrick Wedgeworth, Kevin Lybarger, Angad Singh, Herbie Duber, and Brian Wood were awarded one of 11 UW Pop Health Tier 1 Pilot Research Grants across the University’s Pop Health initiatives. The project, “Patient acceptability of clinical suggestion of social needs automatically identified from clinical notes in the electronic health record” will engage community partners, clinical champions, and primary care patients at UW Medicine to inform informatics strategies that facilitate social determinant of health (SDoH) screening.

Mike Leu, Natalie Pageler (Stanford) and Samuel Yang (graduated CI fellow from Nationwide Children’s) were honored together today as the 2022 Innovator of the Year (an award for the physician informatician that has made a regional/national impact for implementation of an innovation in informatics that has shown positive outcomes towards the advancement of the practice of medicine).

This award was given by the Physicians in AMIA (American Medical Informatics Association). Our innovation was successfully creating/running the first electronic match for clinical informatics fellowship programs (replacing a phone call-based/manual simultaneous-offer process), based on the applicant-favoring NRMP algorithm, that successfully addressed the complex admission constraints resulting from being able to accept applicants from different medical specialties (but only being able to train specific combinations of applicants due to how programs are funded).

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

May 16 – 20, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, May 26th at 11:00 am

Presenter: A. Fischer Lees, MD

Research Fellow, National Library of Medicine

Department of Biomedical and Health Informatics

Title: Improving Medical Training through Secondary Use of EHR data

*Speaker Will Be In-Person: SLU, BLDG C, Room C123A/B

Via Zoom: https://washington.zoom.us/my/peter.th

PUBLICATIONS

Oh, E., Laine, M., Kearns, W., Demiris, G., & Thompson, H.J. (2022). Perceptions of and experiences with consumer sleep technologies that use artificial intelligence. Sensors, 22, 3621. https://doi.org/10.3390/s22103621 

Chen, A. T., Teng, A. K., Zhao, J., Asirot, M. G., Turner, A. M. (accepted). The use of visual methods to support communication with older adults with cognitive impairment: A scoping review. Geriatric Nursing.

Chen, A. T., Johnny, S., Conway, M. (accepted). Examining stigma relating to substance use and contextual factors in social media discussions. Drug and Alcohol Dependence Reports.

Citrenbaum, C., Chen, A. T., & Conway, M. (accepted). Substance use disorder-related stigma: A study of search behavior using Google Trends (2004-2020). American Journal of Drug and Alcohol Abuse

UPCOMING GENERAL EXAM

Meredith Wenjun Wu

Date: May 25, 2022

Time: 10:00 am – 11:30 am

Zoom Link: https://washington.zoom.us/j/99013780442

Title: Semantics-informed Co-Attention Transformers for Whole Slide Skin Biopsy Image Diagnosis

Abstract: Diagnosing melanoma is one of the most challenging areas of pathology with extensive intra- and inter-observer variability. The gold standard for a diagnosis of invasive melanoma is the examination of histopathological whole slide skin biopsy images at both the cellular and structural level by an experienced dermatopathologist. Semantic segmentation, which involves identifying clinically important structures in skin biopsies is an important step toward an accurate diagnosis. Despite recent advancements in multiple instance learning (MIL) scheme which aggregates information from entire WSIs in a single shot, learning representations that reflect the content and context of gigapixel WSIs remains an open and challenging problem.

My dissertation work aims to address the challenge of 1) high computational complexity of end-to-end learning using gigapixel WSIs; 2) the ambiguity between diagnostic categories in a small dataset; and 3) efficient learning from sparse and noisy semantic information. In this proposal, I summarize the preliminary work of 1) semantic segmentation, 2) a transformer-based holistic attention network (HATNet) that uses self-attention to encode global information based on the bag-of-words model, and 3) a scale-aware transformer network (ScAtNet) that learn representations from WSIs at multiple resolutions. Finally, I propose a novel Semantics-informed Co-Attention Transformers (SiCAT) framework that extends HATNet and ScAtNet to learn interpretable and dense co-attention mappings between WSIs and corresponding semantic segmentations. SiCAT will efficiently learn to identify and aggregate informative instances from a large set of bag instances from WSIs.

UPCOMING FINAL EXAMS

Grace Turner

 Date: May 24, 2022

Time: 2:00 pm – 3:30 pm

Zoom Link:  https://washington.zoom.us/j/2763602696

Title: The Use of Natural Language Processing and Machine Learning for Early Diagnosis of Lung and Ovarian Cancer

Abstract: Early diagnosis of cancer is a component of effective treatment. Earlier diagnosis is correlated with higher survival rates following treatment. For many cancers, there are no recommended general population screening tests. Without such tests, providers rely on symptoms to diagnose patients. Such symptoms are primarily detailed within free text clinical notes, and require normalization prior to use. Thus, there is a clear need for natural language processing to extract symptoms for diagnostic work. However, the reliance on symptoms as an early warning sign can be challenging as many cancers have a complex symptomatic diagnostic profile. This creates opportunity for machine learning to help stratify patients. Two such cancers are lung and ovarian cancer, the focus of this work.

In this work, we adapted a symptom extraction model to two different cancer contexts. We then extracted symptoms and developed a retrospective case-control study exploring symptom incidence for ovarian cancer across different routes to diagnosis. Finally, we ran experiments with machine learning models to predict lung and ovarian cancer.  As part of this work, we uncovered a pattern in both cohorts of significantly higher “next step” referrals over six months prior to diagnosis as compared to controls.

 

Aakash Sur

Date: June 3, 2022

Time: 11:00 am – 12:30 pm

Zoom Link:  https://washington.zoom.us/j/93008828511

Title: Data Driven Methods for Scaffolding Genomes with Hi-C

Abstract: High-quality reference genomes are once again in vogue with the publication of the telomere-to-telomere human genome and several challenging plant and animal genomes. Latest efforts around genome assembly have coalesced around two key technologies – ultra long reads and genome chromatin conformation capture (Hi-C). Here, we used both to complete the protist genomes of L. donovani, L. tarentolae, C. fasciculata, and E. gracilis, shedding light on their genomic organization and evolutionary history. To navigate the many Hi-C genome scaffolding methods, we benchmarked the most popular methods against a set of high-quality reference genomes. We found that while most can operate well under ideal circumstances, many struggle with using modern high-quality assemblies which contain near chromosome length contigs. Finally, we attempted to overcome these limitations using a machine learning approach by leveraging the recent bounty of genomes that have been published with Hi-C. Using an innovative convolutional neural network, we demonstrated a proof of concept for a data driven approach to scaffolding genomes.

ANNOUNCEMENTS

Please join us in welcoming Marni Levy as the newest member of the Administrative Core Team. Marni will be the new Graduate Program Advisor for our BHI Academic Program and will begin her position with us on June 1st. Marni is a long-time UW employee who is currently the Program Manager for the Adult Geriatric Doctor of Nursing Practice Program in the Biobehavioral Nursing and Health Informatics Department in the School of Nursing.

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

May 9 – 13, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, May 19th at 11:00 am

Presenter: John Gennari, PhD

Professor, Department of Biomedical Informatics and Medical Education

Title: The Center for Reproducible Biomedical Models: An update

Via Zoom: https://washington.zoom.us/my/peter.th

PUBLICATIONS

Sabin, J. A., Lee, D., Mohammed, S. A., Kett, P. M., Frogner, B. K.. Frontline healthcare providers’ perspectives on stigmatization of COVID-19. 2022 AAMC Health Workforce Conference: Virtual Meeting, [Poster presentation], May 4-6,2022.

Sabin, J. A., Guenther, G., York, B. Barrington, W., Ma, K., Frogner, B. K. Lasting Effects of Brief Implicit Bias Education for Academic Clinicians: From Learning to Action, 2022 AAMC Health Workforce Conference: Virtual Meeting. [Oral presentation] May 4-6, 2022

  1. Zhang, G. Luo. Error and Timeliness Analysis for Using Machine Learning to Predict Asthma Hospital Visits: Retrospective Cohort Study. JMIR Medical Informatics, 2022.
UPCOMING GENERAL EXAM

Meredith Wenjun Wu

Date: May 25, 2022

Time: 10:00 am – 11:30 am

Zoom Link: https://washington.zoom.us/j/99013780442

Title: Semantics-informed Co-Attention Transformers for Whole Slide Skin Biopsy Image Diagnosis

Abstract: Diagnosing melanoma is one of the most challenging areas of pathology with extensive intra- and inter-observer variability. The gold standard for a diagnosis of invasive melanoma is the examination of histopathological whole slide skin biopsy images at both the cellular and structural level by an experienced dermatopathologist. Semantic segmentation, which involves identifying clinically important structures in skin biopsies is an important step toward an accurate diagnosis. Despite recent advancements in multiple instance learning (MIL) scheme which aggregates information from entire WSIs in a single shot, learning representations that reflect the content and context of gigapixel WSIs remains an open and challenging problem.

My dissertation work aims to address the challenge of 1) high computational complexity of end-to-end learning using gigapixel WSIs; 2) the ambiguity between diagnostic categories in a small dataset; and 3) efficient learning from sparse and noisy semantic information. In this proposal, I summarize the preliminary work of 1) semantic segmentation, 2) a transformer-based holistic attention network (HATNet) that uses self-attention to encode global information based on the bag-of-words model, and 3) a scale-aware transformer network (ScAtNet) that learn representations from WSIs at multiple resolutions. Finally, I propose a novel Semantics-informed Co-Attention Transformers (SiCAT) framework that extends HATNet and ScAtNet to learn interpretable and dense co-attention mappings between WSIs and corresponding semantic segmentations. SiCAT will efficiently learn to identify and aggregate informative instances from a large set of bag instances from WSIs.

UPCOMING FINAL EXAM

Grace Turner

 Date: May 24, 2022

Time: 2:00 pm – 3:30 pm

Zoom Link:  https://washington.zoom.us/j/2763602696

Title: The Use of Natural Language Processing and Machine Learning for Early Diagnosis of Lung and Ovarian Cancer

Abstract: Early diagnosis of cancer is a component of effective treatment. Earlier diagnosis is correlated with higher survival rates following treatment. For many cancers, there are no recommended general population screening tests. Without such tests, providers rely on symptoms to diagnose patients. Such symptoms are primarily detailed within free text clinical notes, and require normalization prior to use. Thus, there is a clear need for natural language processing to extract symptoms for diagnostic work. However, the reliance on symptoms as an early warning sign can be challenging as many cancers have a complex symptomatic diagnostic profile. This creates opportunity for machine learning to help stratify patients. Two such cancers are lung and ovarian cancer, the focus of this work.

In this work, we adapted a symptom extraction model to two different cancer contexts. We then extracted symptoms and developed a retrospective case-control study exploring symptom incidence for ovarian cancer across different routes to diagnosis. Finally, we ran experiments with machine learning models to predict lung and ovarian cancer.  As part of this work, we uncovered a pattern in both cohorts of significantly higher “next step” referrals over six months prior to diagnosis as compared to controls.

ANNOUNCEMENTS

Please join us in welcoming Marni Levy as the newest member of the Administrative Core Team. Marni will be the new Graduate Program Advisor for our BHI Academic Program and will begin her position with us on June 1st. Marni is a long-time UW employee who is currently the Program Manager for the Adult Geriatric Doctor of Nursing Practice Program in the Biobehavioral Nursing and Health Informatics Department in the School of Nursing.

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

April 25 – 29, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, May 5th at 11:00 am

Presenter: Valerie Daggett, PhD. Professor, Department of Bioengineering

Title: Dynameomics: From MD simulations of all protein folds to the discovery of a new protein structure linked to toxicity

In-Person: Presenter will be attending in person: SLU C123 A&B

Via Zoom: https://washington.zoom.us/my/peter.th

ANNOUNCEMENTS

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

April 18 – 22, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, April 28st at 11:00 am

Presenter: Linda Shapiro, PhD. Professor, ENG: Computer Science and Engineering, Professor, Paul G. Allen School of Computer Science & Engineering, Adjunct Professor, Biomedical Informatics and Medical Education Professor, Electrical and Computer Engineering

Theme: Imaging Informatics

Via Zoom: https://washington.zoom.us/my/peter.th

PUBLICATIONS

Zagury-Orly Ivry MMSc; Campos-Zamora Melissa MBBS, MMSc; Cadieux Magalie MD, MMSc;

Dzara Kristina PhD, MMSc. Effectively Planning a Journal Club in Academic Medicine. ePub https://journals.lww.com/academicmedicine/Citation/9900/Effectively_Planning_a_Journal_Club_in_Academic.38.aspx

 Dr. Tom Payne is author of a chapter titled “EHR system selection and implementation.”, to appear in the book Biomedical and Health Informatics: Practical Guide, 8th Edition.  Hoyt RE and Hersh WH (eds.), 2022.

Ali M, Liu Z, Taylor M, Orcutt T, Bledsoe A, Phuong J, Stansbury LG, Arbabi S, Robinson B, Bulger E, Vavilala MS, Hess JR. Blood product availability in the Washington State trauma system. Transfusion. [Accepted for Publication on 18 Apr 2022].

Cooper Z, Herrera-Escobar JP, Phuong J, Braverman MA, Bonne S, Knudson MM, Rivara FP, Rowhani-Rahbar A, Price MA, Bulger EM, NTRAP Injury Prevention Panel. Developing a National Trauma Research Action Plan (NTRAP): Results from the Injury Prevention Research Gap Delphi Survey. J Trauma Acute Care Surg. 2022. [Accepted for Publication on 16 Apr 2022]

Joseph B, Saljuqi AT, Phuong J, Shipper E, Braverman MA, Bixby PJ, Price MA, Barraco RD, Cooper Z, Jarman M, Lack W. Developing a National Trauma Research Action Plan (NTRAP): Results from the Geriatric Research Gap Delphi Survey. Journal of Trauma and Acute Care Surgery. 2022 Apr 8:10-97. Published 8 Apr 2022. Available at: https://doi.org/10.1097/TA.0000000000003626

Phuong J, Zampino E, Dobbins N, Espinoza J, Meeker D, Spratt H, Madlock-Brown C, Weiskopf NG, Wilcox A. Extracting Patient-level Social Determinants of Health into the OMOP Common Data Model. InAMIA Annual Symposium Proceedings 2021 (Vol. 2021, p. 989). American Medical Informatics Association. Published 2022 Feb 21. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8861735/

Madlock-Brown C, Wilkens K, Weiskopf N, Cesare N, Bhattacharyya S, Riches NO, Espinoza J, Dorr D, Goetz K, Phuong J, Sule A. Clinical, social, and policy factors in COVID-19 cases and deaths: methodological considerations for feature selection and modeling in county-level analyses. BMC Public Health. 2022 Dec;22(1):1-3. Published 14 Apr 2022. Available at: https://doi.org/10.1186/s12889-022-13168-y

ANNOUNCEMENTS

Lucy Wang, PhD, a graduate of our program in 2019 will join UW faculty as an Assistant Professor in the Information School this Fall. Congratulations to Lucy and we look forward to collaborating with you in the near future!

 (in)Visibility Photo Exhibition: While often overlooked and underappreciated, custodians are the protectors of our shared spaces. Please visit a photo exhibit that features photographs taken by 16 custodial staff members who share the stories of the health impacts of their workplace, neighborhoods and homes. The exhibit will run from April 18 to June 10, 2022 and is located in the T-Wing on the 4th Floor, in the hallway adjacent to the Overpass Café. To learn more, please visit www.uwcustodianproject.com.

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

April 10 – 15, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, April 21st at 11:00 am

Presenter: Eric Horvitz, MD, PhD. Chief Scientific Officer, Microsoft and Affiliate Associate Professor, University of Washington

Title: People, Machines, and Intelligence: Pathways to Deeper Human-AI Synergy

Via Zoom: https://washington.zoom.us/my/peter.th

PUBLICATIONS

Estee Y Cramer, Evan L Ray, Velma K Lopez, Johannes Bracher, Andrea Brennen, Alvaro J Castro Rivadeneira, Aaron Gerding, Tilmann Gneiting, Katie H House, Yuxin Huang, Dasuni Jayawardena, Abdul H Kanji, Ayush Khandelwal, Khoa Le, Anja Mühlemann, Jarad Niemi, Apurv Shah, Ariane Stark, Yijin Wang, Nutcha Wattanachit, Martha W Zorn, Youyang Gu, Sansiddh Jain, Nayana Bannur, Ayush Deva, Mihir Kulkarni, Srujana Merugu, Alpan Raval, Siddhant Shingi, Avtansh Tiwari, Jerome White, Neil F Abernethy,

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Proceedings of the National Academy of Sciences of the United States of America 119 (15), e2113561119, 2022

ANNOUNCEMENTS

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

April 4 – April 8, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: No Class 4/14/22

ANNOUNCEMENTS

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

March 28 – April 1, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, April 7th at 11:00 am

Presenter: Timothy Miller, PhD. Faculty, Computational Health Informatics Program, Boston Children’s Hospital. Assistant Professor, Department of Pediatrics, Harvard Medical School

Title: Representation Learning for Natural Language Processing of Unstructured Text in Electronic Health Records

Via Zoom: https://washington.zoom.us/my/peter.th

The Medical Data Science Seminar: Monday, April 4th at 1:00 pm

Presenter: Ruth Etzioni, PhD, Professor, Public Health Sciences Division, Rosalie and Harold Rea Brown Endowed Chair, Fred Hutch

Title: Using one (big) cancer data resource to help another: Recurrence using Claims And Patient-reported outcomes for SEER Enhancement

Via Zoom: https://washington.zoom.us/j/97026956385?pwd=RmZBdmFyek9ZdHFibUo0aXVrdXJPQT09

PUBLICATIONS

Backonja U, Park SE, Kurre A, Yudelman H, Heindel S, Schultz M, Whitman G, Turner AM, Marchak NT, Bekemeier B. Supporting rural public health practice to address local-level social determinants of health across Northwest states: Development of an interactive visualization dashboard. Journal of Biomedical Informatics. 129(2022):104051. https://doi.org/10.1016/j.jbi.2022.104051

Jiang S, Mathias PC, Hendrix N, Shirts BH, Tarczy-Hornoch P, Veenstra DL, et al. Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis. In press at The Pharmacogenomics Journal, March 2022.

ANNOUNCEMENTS

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.

 

March 21 – March 25, 2022

UPCOMING LECTURES AND SEMINARS

BIME 590: Thursday, March 31st at 11:00 am

Presenter: TBA

Via Zoom: https://washington.zoom.us/my/peter.th

ANNOUNCEMENTS

The Administrative Core Staff are working onsite at SLU on Thursdays and remotely the remaining days of the week. We are currently recruiting for a Graduate Program Advisor, Clinical Informatics Fellowship Administrator and a Fiscal Specialist.