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June 23, 2021
Clinical Informatics Roundtable

About the Clinical Informatics Roundtable

Our long-term goal is to create a supportive community that encourages knowledge sharing and productive collaborations. In doing so, we can raise the tide for all boats. We believe that across the Feinberg School of Medicine, Northwestern Medicine, and the wider Northwestern campus, we have critical mass to be a leader in Clinical Informatics.

The Clinical Informatics Roundtable series will help identify areas of alignment and provide opportunities to:

  • Share your works in progress
  • Learn about exciting new initiatives (academic and in industry)
  • Present thorny challenges
  • Highlight clever insights

All are welcome, recognizing that great ideas can—and even more often do—cross over disciplines.

How to Join

Roundtable discussions are held bimonthly:

  • 3rd Wednesdays of the month from 2pm-3pm CT
  • 4th Thursday of the month from 5pm-6pm CT

You are welcome to join either one or both sessions. Please let us know your availability via the below sign-up form, and we will send you a calendar invite. 

Sign Up for the Clinical Informatics Roundtable
2021 Big Ten Augmented Intelligence Bowl

Big Ten Augmented Intelligence Bowl Featured in Feinberg News

Feinberg News recently published an article about the Big Ten Augmented Intelligence Bowl! The article, "Inaugural ‘AI Bowl’ Aims to Address Health Disparities" by Melissa Rohman, provides a great overview of the event, including a summary of the recent semifinals.
Read the Article
View & Share our Tweet about the Article View & Share our Tweet about the Article

Semifinals Recording Now Available on YouTube

The Big Ten Augmented Intelligence Bowl Semifinals were held on April 30th, 2021. The event featured a keynote address by Rupert M. Evans Sr., MPA, DHA, LFACHE, Professor Emeritus of the Master of Health Administration Program at Governors State University. 
Visit the I.AIM YouTube channel (I.AIM_NUFeinbergMed) for the full playlist.

Visit the Big Ten AI Bowl Website for Updates

As a reminder, the Big Ten Augmented Intelligence Bowl website is frequently updated with important dates, workshop information, upcoming seminars, and more!
Visit the Big Ten AI Bowl Website
Big Ten Augmented Intelligence Bowl Education Series

Workshop for Teams & Mentors: Introduction to AI Bias, AI Principles, and Emerging AI Law with Dan Linna Jr.

Thursday, July 8 | 12:00–2:00 pm (CT)

Daniel W. Linna Jr. is Senior Lecturer and Director of Law and Technology Initiatives at Northwestern Pritzker School of Law. This workshop is closed to the public. Only the competing teams and their mentors will be given the registration information.

If you are a mentor or Big Ten AI Bowl team, you should have received a link via email. Please contact Meg if you have any questions.

I.AIM Seminar Series Presents: Ethics with Anita Ho & Kelly Michelson

Wednesday, July 14 | 12:00–1:00 pm (CT)

Anita Ho, PhD, MPH, Associate Professor at the Centre for Applied Ethics at The University of British Columbia (UBC) and in the Bioethics Program at the University of California San Francisco (UCSF), and a Scientist at the Centre for Health Evaluation and Outcome Sciences (CHÉOS), will join Kelly Michelson, MD, MPH, Chief Ethics Officer at I.AIM and Director of the Center for Bioethics & Medical Humanities for a discussion on ethics. 
Register for Ethics Webinar
Center Spotlight

About the Center for Computational Imaging & Signal Analytics in Medicine (CISAM)

Our center is technology-focused and spans diverse applications in healthcare that generate images and sensor data. The Center for Computational Imaging & Signal Analytics in Medicine brings together expertise in medicine, computing, engineering and informatics to address all stages of the life cycle of machine learning systems, from development to validation and deployment. Our programs reflect Northwestern's research strengths in cardiovascular medicine, digital pathology, radiology and mobile health and sensors.
Learn More About CISAM

Project Highlights

Image Source: DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set (Radiology)
Image Source: Charting a future course for computational pathology

Detection of COVID from chest xrays.

Ramsey Wehbe, MD from Cardiology and Aggelos Katsaggelos, PhD, Joseph Cummings Professor of Electrical Engineering have developed a system to rapidly screen patients for COVID through AI analysis of chest xrays. The study, published in the journal Radiology, utilized over 17,000 chest xray images with 5400 images coming from sites across the Northwestern Healthcare System. Dr. Wehbe is an AI fellow in the Bluhm Cardiovascular Institute and a student in the Masters of Science in Artificial Intelligence Program.

Prognostic scoring of breast cancers.

Mohamed Amgad, MD and Lee Cooper, PhD, Associate Professor of Pathology are developing a system to predict clinical outcomes from whole-slide images of breast cancer tissues. This system uses computer vision to measure growth patterns, immune infiltration, and the reactivity of cancer-adjacent normal tissues to calculate a prognostic score that is accurate and reproducible. The goal of this work is to better predict outcomes in subtypes of breast cancers where prognostication is difficult. This work is done in collaboration with the International Immuno-oncology Biomarker Working Group.
Image Source: IVPL Katsaggelos Lab
Image Source: HABits Lab

Screening head CT images for emergencies.

Virginia Hill, MD, Assistant Professor of Radiology is developing an AI system to detect and triage emergencies in head CT imaging. The project, which is funded by the Dixon Translational Research Grants Initiative, aims to detect 21 distinct emergencies from head CT including intracranial hemorrhage and mass effect and will allow triaging of exams and alerts to the radiologist of life-threatening findings. This tool will improve patient safety by moving positive exams to the top of the list for the radiologist to read, reducing time until patient treatment is initiated. This project is a collaboration among multiple center members including Todd Parrish, PhD from Radiology and Aggelos Katsaggelos, PhD from Electrical and Computer Engineering.

Monitoring health risk behaviors using wearable devices.

Nabil Alshurafa, PhD, Assistant Professor of Preventative Medicine is developing a wearable device to monitor health-risk behaviors such a smoking, consuming alcohol, and medication adherence. BehaviorSight will overcome the bias and inaccuracy of self-reporting risk behaviors and enable appropriate behavioral interventions in real time. This system will use a self-worn video device to detect hand-to-mouth gestures in an unobtrusive package that is privacy-conscious. This research is supported by a NIBIB R21 Trailblazer Award.
Image Source: Northwestern CPLUSR

AI in Medical Imaging Group Meeting

Monthly | Next Meeting: July 15, 2021

Once a month, this group would like to return to opening up their weekly lab meetings to draw radiologists and other clinicians to discuss AI and possible projects. This monthly meeting brings together MDs, radiologists, and engineers to foster collaboration and discuss projects that apply AI to imaging problems. This meeting will resume July 15th via Zoom. Please contact Virginia Hill for details (virginia.hill@nm.org).

Select Publications

  1. Besson P, Parrish T, Katsaggelos AK, Bandt SK. Geometric deep learning on brain shape predicts sex and age. Computerized Medical Imaging and Graphics. 2021 May 27:101939.
  2. Wehbe RM, Sheng J, Dutta S, Chai S, Dravid A, Barutcu S, Wu Y, Cantrell DR, Xiao N, Allen BD, MacNealy GA. DeepCOVID-XR: an artificial intelligence algorithm to detect COVID-19 on chest radiographs trained and tested on a large US clinical data set. Radiology. 2021 Apr;299(1):E167-76.
  3. D. Shen, S. Ghosh, H. Haji-Valizadeh, A. Pathrose, F. Schiffers, D. C. Lee, B. H. Freed, M. Markl, O. S. Cossairt, A. K. Katsaggelos, D. Kim, “Rapid reconstruction of highly undersampled, non-Cartesian real-time cine k-space data using a perceptual complex neural network (PCNN),” NMR in Biomedicine, 2021; 34:e4405
  4. Mobadersany P, Cooper LA, Goldstein JA. GestAltNet: aggregation and attention to improve deep learning of gestational age from placental whole-slide images. Laboratory Investigation. 2021 Mar 5:1-0.
  5. He B, Song Y, Wang L, Wang T, She Y, Hou L, Zhang L, Wu C, Babu BA, Bagci U, Waseem T. A machine learning-based prediction of the micropapillary/solid growth pattern in invasive lung adenocarcinoma with radiomics. Translational Lung Cancer Research. 2021 Feb;10(2):955.
  6. LaLonde R, Xu Z, Irmakci I, Jain S, Bagci U. Capsules for biomedical image segmentation. Medical image analysis. 2021 Feb 1;68:101889.
  7. Lee S, Amgad M, Mobadersany P, McCormick M, Pollack BP, Elfandy H, Hussein H, Gutman DA, Cooper LA. Interactive classification of whole-slide imaging data for cancer researchers. Cancer Research. 2021 Feb 15;81(4):1171-7.
  8. Wakschlag L, Tandon D, Krogh-Jespersen S, Petitclerc A, Nielsen A, Ghaffari R, Mithal L, Bass M, Ward E, Berken J, Fareedi E, Cummings P, Mestan K, Norton E, Grobman W, Rogers J, Moskowitz J, Alshurafa N. Moving the Dial on Prenatal Stress Mechanisms of Neurodevelopmental Vulnerability to Mental Health Problems: A Personalized Prevention Proof of Concept. Developmental Psychobiology. 2020; 00: 1-19. doi: 10.1002/dev.22057.
  9. Zhang S, Zhao Y, Nguyen D, Xu R, Sen S, Hester J, Alshurafa N. NeckSense: A Multi-sensor Necklace for Detecting Eating Activities in Free-Living Conditions. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2020 *Best paper award
  10. Zhang S, Xu Q, Sen S, Alshurafa N. VibroScale: Turning Your Smartphone into a Weighing Scale. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) 2020. doi: org/10.1145/3410530.3414397 *Best paper award

Select Awards

  • NIBIB K08EB030120 – Developing a virtual placenta biobank (Goldstein, Pathology)
  • NIBIB R21EB030305 - BehaviorSight: Privacy enhancing wearable system to detect health risk behaviors in real-time (Alshurafa, Preventative Medicine / Katsaggelos, ECE)
  • NIDDK R03DK127128 - WildCam: A Privacy Conscious Wearable Eating Detection Camera People will Actually Wear in the Wild (Alshurafa, Preventative Medicine)
  • Siemens - Neural Network 3D Detector Response-Feasibility and Optimization (Katsaggelos, ECE)
  • NCI R01CA240639– Radiologist-Centered Artificial Intelligence (RCAI) for Lung Cancer Screening and Diagnosis (Bagci, Radiology)
  • NIBIB R21EB030806 - Next-Generation Cardiovascular MRI powered by Artificial Intelligence (Kim, Radiology / Katsaggelos, ECE)
Get to Know the I.AIM Team

Welcome, Katie!

Katie Snarich joined the I.AIM team this month as our Communications Intern! Katie is a rising sophomore at the University of Illinois at Urbana-Campaign. With an interest in a career in the media space, she is pursuing a degree in advertising. 

Katie will work with Mara and the I.AIM team to promote the work of I.AIM through social media, the website, and our newsletter.

I.AIM Membership
Are you interested in becoming more involved in I.AIM initiatives? Become a member!
Membership Form
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Look for next month's spotlight Center: Center for Biomedical Informatics & Data Science (CBIDS) with Dr. Starren!
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