Staff Spotlight #3
![HACLab logo](/sites/default/files/styles/wide/public/2024-06/haclab-logo-mark-full-color-rgb-1500px%4072ppi%20%281%29_0.jpg?itok=eAGzByz_)
ASCO 2024 Annual Meeting Highlights
We were well-represented at the American Society of Clinical Oncology 2024 Annual Meeting with a total of 9 abstracts presented.
![RaviASCO](/sites/default/files/inline-images/RaviASCO2.jpg)
![RaviASCO2](/sites/default/files/inline-images/RaviASCO1.jpg)
![RaviGabeASCO](/sites/default/files/inline-images/RaviGabeASCO.jpg)
![RamyASCO](/sites/default/files/inline-images/RamyASCO.jpg)
![MartinASCO](/sites/default/files/inline-images/MartinASCO.jpeg)
Other News
Director Ravi Parikh was appointed to The National Academies of Sciences, Engineering, and Medicine and will be presenting at two upcoming workshops:
- Human and Organizational Factors in AI Risk Management: Workshop 3 (Safety in Context: Culture, Processes, and Frameworks) on June 26th
- Human and Organizational Factors in AI Risk Management: Workshop 4 (Designing Paths Forward in AI Risk Management) on July 2nd
Likhitha Kolla, John Lin, and Xavier Orcutt presented at the Symposium on Artificial Intelligence for Learning Health Systems in May 2024 in Puerto Rico! Likhitha presented work on algorithm reliability; John presented work on AI regulation; and Xavier presented work on AI-based trial emulation.
Tamar Klaiman, Jenna White, Caleb Hearn, Amaya Diana, Will Ferrell, and Ravi Parikh integrated qualitative research methods via semi-structured interviews followed by detailed coding and analysis in two white papers. In the first, we interviewed 23 clinicians from multiple specialties to capture perspectives to design an effective virtual palliative care program. In the second, we interviewed administrators and providers to learn how they envision palliative care and the relationship between hospice and palliative care.
HACblogs have been active. Will Ferrell summarized our portfolio of Patient-Generated Health Data in a March issue. Caleb Hearn and team wrote “Statistical Concepts and Metrics of Algorithm Bias and Fairness” exploring how bias in algorithms is identified and quantified according to statistical concepts and metrics in a follow up to the first in the series. Caleb also authored a thought piece summarizing this line of work for MEHP Online Education website: HACLab: Mitigating Bias in Machine Learning and AI Programming.
Follow us on Linkedin and Twitter @HACLab_UPenn for regular updates.