What We Do

AI mimics human intelligence to support healthcare workers through improving diagnosis and... Read more
While healthcare algorithms can improve prediction and diagnosis, they often “bake in” bia... Read more
While most healthcare data comes from claims and electronic health record “exhaust”, incre... Read more
Real-world data is data that is generated through routine health operations, often in the ... Read more
Cancer care is in the midst of a revolution in digital health innovations, payment reform,... Read more

Our Approach

  • Develop
    • Train and validate predictive and diagnostic algorithms using real-world data
  • Plan
    • Quantitative and mixed-methods exploration to identify optimal use cases and implementation strategies
  • Test
    • Implementation and prospective evaluation of algorithm-enabled interventions
  • Scale
    • Scaling algorithms for clinical impact

HAC Blog

March 09, 2023

Welcome to the Human-Algorithm Collaboration Lab (HACLab)!

Founded at the Perelman School of Medicine and the Abramson Cancer Center at the University of Pennsylvania, we are a laboratory focusing on the development, validation, implementation, and scaling of advanced algorithms in clinical care and health policy.

What is..

Machine learning?

Cancer survivorship?

Algorithm unfairness?

Real World Data?

Patient Generated Health Data?

A branch of AI and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy (source:IBM)

The health and well-being of a person with cancer from the time of diagnosis until the end of life. This includes issues related to follow-up care, late effects of treatment, cancer recurrence, second cancers, and quality of life (source:cancer.gov)

Systematic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. It also, occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process (source:FSU)

The data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources- electronic health records (EHRs), claims and billing activities, pghd, product and disease registries (source:FDA)

 Health-related data created, recorded, or gathered by or from patients (or family members or other caregivers) to help address a health concern (source:healthit)

Contact Us

Interested in collaborating with the HACLab? Please complete the form below with questions, comments, and suggestions.

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