Entomologist Jessica Ware is using new technologies to identify insect species in a changing climate. She shares her suggestions for how we can live harmoniously with creeper crawlers everywhere.
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Entomologist Jessica Ware
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Maybe it feels like a core human instinct to demonize bugs as gross. We seem to try to eradicate them in every way possible, whether that’s with poison, or getting out our blood thirst by stomping them whenever they creep and crawl into sight.
But where did our fear of bugs really come from? Jessica makes a compelling case that a lot of it is cultural, rather than in-born, and we should be following the lead of other cultures that have learned to live with and appreciate bugs.
The truth is that a healthy planet depends on insects. You may feel stung by that news if you hate bugs. Reality bites.
Jessica and I talk about whether learning to live with insects should include eating them and gene editing them so they don’t transmit viruses. She also tells me about her important research into using genomic tools to track bugs in the wild to figure out why and how we’ve lost 50 percent of the insect population since 1970 according to some estimates – bad news because the ecosystems that make up the planet heavily depend on insects. Jessica is leading the way to better understand what’s causing these declines in order to start reversing these trends to save the insects and to save ourselves.
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.