Impact AI Personalized Cancer Treatment Decisions with Nathan Silberman from Artera
Being given a cancer diagnosis is one of the worst pieces of news you can receive as a patient. This is often made even more difficult by the fact that choosing a treatment option is rarely simple or easy. Clinicians need to make multiple assessments before they can move forward, and even then it is often difficult or impossible to make unambiguous predictions. That’s where Artera comes in, a company using multimodal AI tests to provide individualized results for cancer patients, which enables clinicians and patients to make personalized treatment decisions, together.
I am joined today by Nathan Silberman, Vice President of Machine Learning and Engineering at Artera, to talk about how Artera’s technology is paving the way for personalized cancer treatment decisions. Join us today, as we get into how Artera is contributing to the cancer treatment process, some of the biggest challenges they face, and how they are addressing these through specifically trained algorithms and robust validation protocols. Be sure to tune in to this important conversation on how Artera is impacting cancer treatment outcomes for the better!
Key Points:
- Background on our guest, Nathan Silberman, and what led him to Artera.
- How Artera is helping clinicians make informed decisions for cancer treatments.
- The role of machine learning in their personalized risk assessments for patients.
- Key challenges they’ve encountered with pathology data.
- How they deal with slide variations through well-trained algorithms.
- Bias in pathology data and what Artera is doing to mitigate bias.
- Their partnerships with academics, clinicians, and oncologists.
- Insight into the variety of approaches they use to validate their models.
- How their tests fit in with clinical workflows and assist doctors and patients.
- The agonizing wait time associated with traditional non-AI testing methods.
- How Artera is providing quick and reliable test results.
- Advice to leaders of AI-powered startups: stay focused on the ultimate goal of patient impact.
- Looking ahead at Artera’s impact in the next three to five years.
Quotes:
“Which therapy to choose is simply not an easy choice. Clinicians would ideally be able to accurately assess a patient's risk of a cancer spreading, or adversely affecting the patient's health in the short term. But often, that's hard or impossible for a clinician to predict.” — Nathan Silberman
“Clinicians have been wanting and waiting for tools that can predict whether or not a therapy will work for that particular patient. This is ultimately where Artera steps in.” — Nathan Silberman
“Rather than wait a month, Artera's test provides the answer within two to three days after the lab receives the biopsy slide. And it is so rewarding to hear from clinicians, and especially patients about the relief we can provide by giving clarity sooner.” — Nathan Silberman
“I think the biggest piece of advice I can give is really just making sure that you're laser-focused on the ultimate goal of patient impact.” — Nathan Silberman
Links:
Resources for Computer Vision Teams:
LinkedIn – Connect with Heather.
Computer Vision Insights Newsletter – A biweekly newsletter to help bring the latest machine learning and computer vision research to applications in people and planetary health.
Computer Vision Strategy Session – Not sure how to advance your computer vision project? Get unstuck with a clear set of next steps. Schedule a 1 hour strategy session now to advance your project.
Foundation Model Assessment – Foundation models are popping up everywhere – do you need one for your proprietary image dataset? Get a clear perspective on whether you can benefit from a domain-specific foundation model.