HAC Blog

Updates from HACLab for June 2024 including highlights from the 2024 ASCO Annual Meeting!

Author: Will Ferrell

This blog highlights patient-generated health data (PGHD) by reviewing a case study of one of our clinical trials: PROStep: A Feasibility Trial Using PROs and Step Data to Monitor Patients With Lung and GI Cancers

Author: Will Ferrell

In the first entry of this series, we examined how algorithms can be biased on a variety of factors, including their underlying data, biased individuals creating models, or from statistical mischaracterizations from models themselves.  In this entry, Caleb Hearn et al. explore how bias in algorithms is identified and quantified according to a few different statistical concepts and metrics.

Authors: Caleb Hearn, Sae-Hwan Park, Ravi Parikh

Updates from the HACLab for October 2023

Author: Will Ferrell

Algorithms leverage existing data to predict an outcome, using inputs that are associated with the outcome.  One problem with the forthcoming tide of machine learning algorithms is that such algorithms can be biased.  In this blog, we start exploring the concept of "Algorithmic Bias"

Author: Caleb Hearn

Algorithms are routinely used in the clinic to make decisions on patient care. Over time these algorithms may deteriorate in performance. Here, we start the explore the concept of “performance drift”.

Author: Likhitha Kolla

Updates from the HACLab for August 2023

Author: Will Ferrell

AI's role in our daily lives continues to become more omnipresent and healthcare is no exception.  As AI becomes more routinely incorporated in healthcare, a central question becomes – how do we regulate it?

Author: Ravi Parikh

Caleb M. Hearn, MPH, CAPM​ will have a podium talk “Hospice Provider Perspectives on Providing Earlier Palliative Care for Patients with Serious Illness”

​Jenna Steckel, MSW will have a poster presentation “Clinician Perspectives on Virtual Palliative Care for Patients with Advanced Illness​”