Submissions Are Now Open for the 2023 Health Equity DataJam!

Submission Deadline: Sunday, April 30, 2023, at 5:00 p.m. ET
https://academyhealth.org/about/programs/health-equity-datajam

For a second year, AcademyHealth is hosting the Health Equity DataJam to harness the power of data and the creativity of the public to answer pressing questions related to health and health care disparities. Participants will transform raw data into actionable insights and digital tools to bridge disparities of health, including those exacerbated by barriers to care, Long COVID, cancer, infection-associated chronic illnesses and kidney and Lyme diseases, to ensure equitable access and wellness for all.

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A Discussion on Race as a Variable in Artificial Intelligence

Moderated by: Benjamin Collins, MD, MA and Rachele Hendricks-Sturrup, DHSc, MSc, MA

Date/Time:Thursday, March 2, 2023, 3-4pm CST

Where: Microsoft Teams (http://bit.ly/3m5Lj1Z)

Peer-reviewed literature and the broader media continue to highlight the risks and challenges as well as the opportunities and benefits of artificial intelligence and machine learning (AI/ML) development, translation, and implementation in health research and practice. For example, recent literature [1] has discussed serious health equity concerns regarding the use of race correction in clinical algorithms spanning across multiple medical specialties including cardiology, cardiac surgery, nephrology, obstetrics, urology, oncology, endocrinology, and pulmonology. Race correction can result in problems such as improper screening/monitoring cadence; inaccurate estimates of organ function, risk adjustments and profiling, and disease risk. Recent news stories have also covered issues around the use of algorithms and machine learning models that inaccurately and inappropriately predict stroke risk in Black (versus White) patients [2]. Lastly, as OpenAI released its ChatGPT chatbot, institutions are considering the use and application of ChatGPT in clinical practice and education with great controversy [3]. The AIM-AHEAD Ethics Sub-Core will host an AIM-AHEAD Ethics Discussion Series about these issues and others, with a goal to drive moderated discussion, ideas, and collaboration within the AIM-AHEAD community on the ethical development, use, and implementation of AI/ML in health research and practice.

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RCMI and AIM-AHEAD Virtual Seminar Series:

Topic: Improving Healthcare with AI: Opportunities & Challenges Across the Spectrum of Care

Speaker: Dr. Jenna Wiens, PhD
Associate Professor of Computer Science and Engineering (CSE) Associate Director of the AI lab Co-Director of Precision Health University of Michigan, Ann Arbor

Date/Time: Thursday, Feb. 16th 2023 from 12p-1p CST via Zoom

Register here: https://us06web.zoom.us/meeting/register/tZwvcuqgrjsqEtRzOu69lwpTVHslTcTa5U8I

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The National Center for Advancing Translational Sciences (NCATS) team launched the Minimizing Bias and Maximizing Long-term Accuracy, Utility, and Generalizability of Predictive Algorithms in Healthcare Challenge, and they want you to create a solution that detects bias in AI/ML models used in clinical decisions!

Learn more and register for free by Feb. 15:
https://expeditionhacks.com/bias-detection-healthcare/

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New course available!

AIM-AHEAD presents "All of Us Researcher Workbench On-Demand Training"

Enroll today in this free, self-directed course that provides an overview of the Researcher Workbench and how it can be used to address health disparities with Artificial Intelligence and Machine Learning.

Learn more and enroll here: https://courses.aim-ahead.net/course/c/AllofUs-on-demand

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Partner Webinar from Howard's RCMI Community Engagement Core and the University of Chicago Data Science Institute:

Topic: Understanding the Sociome

Description: A complete set of a person's genetic material is called a genome. Recently, the term "sociome" has been used to describe a person's combined social, environmental, behavioral, and psychological lived experiences. The sociome plays a critical role in human health. Join the Howard RCMI Community Engagement Core and the University of Chicago Data Science Institute for a discussion of the sociome and the potential for this emerging branch of data science to transform modern healthcare.

Date/Time: January 17, 2023 from 2-3p ET

Register here: https://howard.zoom.us/meeting/register/tZcrce-qpj8iGtSFfQLuwL4VX2-W95Pp9snx

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January is National Mentoring Month! AIM-AHEAD and the National Research Mentoring Network (NRMN) are partnering to celebrate National Mentoring Month. This year we have a theme for each week and are hosting a Twitter Chat and two Webinars. Follow us on the AIM-AHEAD Socials and check out the events calendar to join us in the celebration!

Mentoring Month Weekly Themes and Special Days:
January 2-6: Benefit of Mentoring
January 9-13: What makes a good mentoring relationship
January 11: I Am a Mentor Day
January 16-20: How to find a mentor and build a network of mentors
January 18: Twitter Chat from 3-4p CT
January 23-31: Thank your mentor
January 23: Webinar - Diverse Mentoring Across STEMM from 12-1p CT
January 25: Webinar - Mentors as Culture-creators: Fostering Inclusion and Belonging through the Mentoring Relationship from 3-4p CT
January 26: Thank Your Mentor Day

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The Skills & Workforce Development Core Proudly Presents the Director for Training on AI/ML Basic Concepts Education Module.

Prof. Wei Wang is the Leonard Kleinrock Chair Professor in Computer Science and Computational Medicine at University of California, Los Angeles (UCLA). She also serves as the Director of the Scalable Analytics Institute (ScAi). Prof. Wang's expertise spans big data analytics, data mining, machine learning, natural language processing, computational biology, and computational medicine. Her recent research focuses on algorithms for discovering complex patterns in largescale, multi-modal, high-dimensional biomedical data. Her team has developed methods in representation learning, knowledge graphs, information integration; and has established broad
collaborations with biomedical researchers and physician scientists. She is the Chair of the ACM Special Interest Group on Knowledge Discovery in Data (SIGKDD). Prof. Wang is a fellow of ACM and IEEE.

Over her 20-year teaching career, Prof. Wang has served as course instructor for over 40 AI/ML courses, at UNC Chapel Hill (2002-2012) and then at UCLA (2012-Present). Over the past 10 years as a UCLA Faculty, Prof. Wang has mentored 30+ Ph.D. students and more than 100 M.S. students, including many URM students. Her trainees have established prosperous careers within both academia and industry. She serves in a leadership capacity for many education programs, e.g., director of the NSF Research Traineeship program on harnessing data revolution at UCLA, a testament to her commitment and dedication in interdisciplinary training in Computational Medicine as well as Data Science.

To join the webinar “Introduction to Basic Elements of AI and ML Part 2” with Prof. Wang this Thursday at 12pm PT/3pm ET, please use this link: https://uclahs.zoom.us/j/92084203374

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The National Science Foundation's Expanding AI Innovation through Capacity Building and Partnerships (ExpandAI) program supports capacity-development projects and partnerships within the National AI Research Institutes ecosystem that help broaden participation in artificial intelligence research, education and workforce development

Learn more at https://beta.nsf.gov/funding/opportunities/expanding-ai-innovation-through-capacity-building

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RCMI and AIM-AHEAD Virtual Seminar Series: A Decade of Molecular Cell Atlases. Thursday, December 8, 2022 from 12-1p CST. See attachment for more information and to register.

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