Artificial Intelligence is getting better than humans at detecting breast cancer
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans 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.
Biohackers Made a Cheap and Effective Home Covid Test -- But No One Is Allowed to Use It
Last summer, when fast and cheap Covid tests were in high demand and governments were struggling to manufacture and distribute them, a group of independent scientists working together had a bit of a breakthrough.
Working on the Just One Giant Lab platform, an online community that serves as a kind of clearing house for open science researchers to find each other and work together, they managed to create a simple, one-hour Covid test that anyone could take at home with just a cup of hot water. The group tested it across a network of home and professional laboratories before being listed as a semi-finalist team for the XPrize, a competition that rewards innovative solutions-based projects. Then, the group hit a wall: they couldn't commercialize the test.
They wanted to keep their project open source, making it accessible to people around the world, so they decided to forgo traditional means of intellectual property protection and didn't seek patents. (They couldn't afford lawyers anyway). And, as a loose-knit group that was not supported by a traditional scientific institution, working in community labs and homes around the world, they had no access to resources or financial support for manufacturing or distributing their test at scale.
But without ethical and regulatory approval for clinical testing, manufacture, and distribution, they were legally unable to create field tests for real people, leaving their inexpensive, $16-per-test, innovative product languishing behind, while other, more expensive over-the-counter tests made their way onto the market.
Who Are These Radical Scientists?
Independent, decentralized biomedical research has come of age. Also sometimes called DIYbio, biohacking, or community biology, depending on whom you ask, open research is today a global movement with thousands of members, from scientists with advanced degrees to middle-grade students. Their motivations and interests vary across a wide spectrum, but transparency and accessibility are key to the ethos of the movement. Teams are agile, focused on shoestring-budget R&D, and aim to disrupt business as usual in the ivory towers of the scientific establishment.
Ethics oversight is critical to ensuring that research is conducted responsibly, even by biohackers.
Initiatives developed within the community, such as Open Insulin, which hopes to engineer processes for affordable, small-batch insulin production, "Slybera," a provocative attempt to reverse engineer a $1 million dollar gene therapy, and the hundreds of projects posted on the collaboration platform Just One Giant Lab during the pandemic, all have one thing in common: to pursue testing in humans, they need an ethics oversight mechanism.
These groups, most of which operate collaboratively in community labs, homes, and online, recognize that some sort of oversight or guidance is useful—and that it's the right thing to do.
But also, and perhaps more immediately, they need it because federal rules require ethics oversight of any biomedical research that's headed in the direction of the consumer market. In addition, some individuals engaged in this work do want to publish their research in traditional scientific journals, which—you guessed it—also require that research has undergone an ethics evaluation. Ethics oversight is critical to ensuring that research is conducted responsibly, even by biohackers.
Bridging the Ethics Gap
The problem is that traditional oversight mechanisms, such as institutional review boards at government or academic research institutions, as well as the private boards utilized by pharmaceutical companies, are not accessible to most independent researchers. Traditional review boards are either closed to the public, or charge fees that are out of reach for many citizen science initiatives. This has created an "ethics gap" in nontraditional scientific research.
Biohackers are seen in some ways as the direct descendents of "white hat" computer hackers, or those focused on calling out security holes and contributing solutions to technical problems within self-regulating communities. In the case of health and biotechnology, those problems include both the absence of treatments and the availability of only expensive treatments for certain conditions. As the DIYbio community grows, there needs to be a way to provide assurance that, when the work is successful, the public is able to benefit from it eventually. The team that developed the one-hour Covid test found a potential commercial partner and so might well overcome the oversight hurdle, but it's been 14 months since they developed the test--and counting.
In short, without some kind of oversight mechanism for the work of independent biomedical researchers, the solutions they innovate will never have the opportunity to reach consumers.
In a new paper in the journal Citizen Science: Theory & Practice, we consider the issue of the ethics gap and ask whether ethics oversight is something nontraditional researchers want, and if so, what forms it might take. Given that individuals within these communities sometimes vehemently disagree with each other, is consensus on these questions even possible?
We learned that there is no "one size fits all" solution for ethics oversight of nontraditional research. Rather, the appropriateness of any oversight model will depend on each initiative's objectives, needs, risks, and constraints.
We also learned that nontraditional researchers are generally willing (and in some cases eager) to engage with traditional scientific, legal, and bioethics experts on ethics, safety, and related questions.
We suggest that these experts make themselves available to help nontraditional researchers build infrastructure for ethics self-governance and identify when it might be necessary to seek outside assistance.
Independent biomedical research has promise, but like any emerging science, it poses novel ethical questions and challenges. Existing research ethics and oversight frameworks may not be well-suited to answer them in every context, so we need to think outside the box about what we can create for the future. That process should begin by talking to independent biomedical researchers about their activities, priorities, and concerns with an eye to understanding how best to support them.
Christi Guerrini, JD, MPH studies biomedical citizen science and is an Associate Professor at Baylor College of Medicine. Alex Pearlman, MA, is a science journalist and bioethicist who writes about emerging issues in biotechnology. They have recently launched outlawbio.org, a place for discussion about nontraditional research.
Sept. 13th Event: Delta, Vaccines, and Breakthrough Infections
This virtual event will convene leading scientific and medical experts to address the public's questions and concerns about COVID-19 vaccines, Delta, and breakthrough infections. Audience Q&A will follow the panel discussion. Your questions can be submitted in advance at the registration link.
DATE:
Monday, September 13th, 2021
12:30 p.m. - 1:45 p.m. EDT
REGISTER:
Dr. Amesh Adalja, M.D., FIDSA, Senior Scholar, Johns Hopkins Center for Health Security; Adjunct Assistant Professor, Johns Hopkins Bloomberg School of Public Health; Affiliate of the Johns Hopkins Center for Global Health. His work is focused on emerging infectious disease, pandemic preparedness, and biosecurity.
Dr. Nahid Bhadelia, M.D., MALD, Founding Director, Boston University Center for Emerging Infectious Diseases Policy and Research (CEID); Associate Director, National Emerging Infectious Diseases Laboratories (NEIDL), Boston University; Associate Professor, Section of Infectious Diseases, Boston University School of Medicine. She is an internationally recognized leader in highly communicable and emerging infectious diseases (EIDs) with clinical, field, academic, and policy experience in pandemic preparedness.
Dr. Akiko Iwasaki, Ph.D., Waldemar Von Zedtwitz Professor of Immunobiology and Molecular, Cellular and Developmental Biology and Professor of Epidemiology (Microbial Diseases), Yale School of Medicine; Investigator, Howard Hughes Medical Institute. Her laboratory researches how innate recognition of viral infections lead to the generation of adaptive immunity, and how adaptive immunity mediates protection against subsequent viral challenge.
Dr. Marion Pepper, Ph.D., Associate Professor, Department of Immunology, University of Washington. Her lab studies how cells of the adaptive immune system, called CD4+ T cells and B cells, form immunological memory by visualizing their differentiation, retention, and function.
This event is the third of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.