Biomedical Data Science Innovation Lab
iTHRIV is excited to share the 2023 Biomedical Data Science Innovation Lab topic:
Data Science and the Public Health Consequences of the COVID-19 Pandemic.
The global COVID-19 pandemic over the past two years has upset our lives in ways unimaginable before we took to wearing masks, isolating at home, and avoiding contact with family, friends, and colleagues.
We are only now, just contending with the secondary effects of COVID exposures – so-called ‘long-haul COVID’ – but also the effects of deferred regular health check-ups, poor mental health, and more.
Can quantitative approaches and data science be useful in not only modeling the pandemic itself but also tracking these secondary effects of the burgeoning global health crises?
The goal of this BDSIL is to foster the formation of new interdisciplinary collaborations which will generate creative strategies for addressing the use of data science approaches for predicting the incidences of health effects secondary to the COVID-19 pandemic.
Read more here: http://www.innovation.lab.virginia.edu/2023-lab
iTHRIV was a proud sponsor of the 2021-2022 Biomedical Data Science Innovation Lab: Ethical Challenges of Artificial Intelligence, held at the Boar's Head Inn from June 13th-17th, 2022
Read the description below and click through slide-show to get a glimpse inside the conference.
Artificial Intelligence (AI) has great potential to assist in biomedical decision making. However, such systems are not immune from making erroneous recommendations, struggling to maintain patient privacy, and which give rise to vexing questions about their suitability across genders, ethnic, or cultural communities. The goal of the 2021-2022 Biomedical Data Science Innovation Lab was to foster the formation of new interdisciplinary collaborations which would generate creative strategies for addressing ethics of artificial intelligence (AI) in biomedicine.
This Biomedical Data Science Innovation Lab intended to bring together expertise from the mathematical, statistical, basic science, and clinical biomedical fields, to address interdisciplinary topics in biomedical data science critical to how AI is implemented in clinical decision making. Members of the NIH-NCATS community are important contributors to these conversations.
The 2021-2022 Biomedical Data Science Innovation Lab sought to highlight the challenges of ethically working with datatypes in support of AI systems and how AI might be made ethical against best practice recommendations. Inter-disciplinary collaborations that formed during the Biomedical Data Science Innovation Lab could result in new peer-reviewed publications or NIH/NSF grant proposals to further develop, refine, and test hypotheses and develop original research project ideas.