An image from one of TRIPP's virtual reality experiences for mental wellness. Nanea Reeves is TRIPP's CEO.
The "Making Sense of Science" podcast features interviews with leading experts about health innovations and the ethical questions they raise. The podcast is hosted by Matt Fuchs, editor of Leaps.org, the award-winning science outlet.
My guest today is Nanea Reeves, the CEO of TRIPP, a wellness platform with some big differences from meditation apps you may have tried like Calm and Headspace. TRIPP's experiences happen in virtual reality, and its realms are designed based on scientific findings about states of mindfulness. Users report feelings of awe and wonder and even mystical experiences. Nanea brings over 15 years of leadership in digital distribution, apps and video game technologies. Before co-founding TRIPP, she had several other leadership roles in tech with successful companies like textPlus and Machinima. Read her full bio below in the links section.
Nanea Reeves, CEO of TRIPP.
TRIPP
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This conversation coincided with National Brain Awareness Week. The topic is a little different from the Making Sense of Science podcast’s usual focus on breakthroughs in treating and preventing disease, but there’s a big overlap when it comes to breakthroughs in optimal health. Nanea’s work is at the leading edge of health, technology and the science of wellness.
With TRIPP, you might find yourself deep underwater, looking up at the sunlight shimmering on the ocean surface, or in the cosmos staring down at a planet glowing with an arresting diversity of colors. Using TRIPP for the past six months has been a window for me into the future of science-informed wellness and an overall fascinating experience, as was my conversation with Nanea.
Show notes:
Nanea and I discuss her close family members' substance addictions and her own struggle with mental illness as a teen, which led to her first meditation experiences, and much more:
- The common perception that technology is an obstacle for mental well-being, a narrative that overlooks how tech can also increase wellness when it’s designed right.
- Emerging ways of measuring meditation experiences by recording brain waves - and the shortcomings of the ‘measured self’ movement.
- Why TRIPP’s users multiplied during the stress and anxiety of the pandemic, and how TRIPP can can be used to enhance emotional states.
- Ways in which TRIPP’s visuals and targeted sound frequencies have been informed by innovative research from psychologists like Johns Hopkins’ Matthew Johnson.
- Ways to design apps and other technologies to better fulfill the true purpose of mindfulness meditation. (Hint: not simply relaxation.)
- And of course, because the topic is mental wellness and tech, I had to get Nanea's thoughts on Elon Musk, Neuralink and brain machine interfaces.
Here are links for learning more about TRIPP:
- TRIPP website: https://www.tripp.com/about/
- Nanea Reeves bio: https://www.tripp.com/team/nanea-reeves/
- Study of data collected by UK's Office for National Statistics on behavior during the pandemic, which suggests that TRIPP enhanced users' psychological and emotional mindsets: https://link.springer.com/chapter/10.1007/978-3-03...
- Research that's informed TRIPP: https://www.tripp.com/research/
- Washington Post Top Pick at CES: https://www.washingtonpost.com/technology/2019/01/...
- TRIPP's new offering, PsyAssist, to provide support for ketamine-assisted therapy: https://www.mobihealthnews.com/news/tripp-acquires...
- Randomized pilot trial involving TRIPP: https://bmjopen.bmj.com/content/bmjopen/11/4/e0441...
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
