Technology & AI

Breast Cancer

Technology & AI

FDA Gives Green Light to MedCognetics’s Breast Cancer Screening AI

Editorial Team

December 20, 2022
3 min read

Study Finds Google’s Kidney Disease AI to be Less Effective on Women in 2019, Google developed an artificial intelligence system that could predict severe kidney injury in patients up to two days in advance. Since kidney-related injuries are a common cause of death among hospitalized patients, the results were met with high hopes for the future. The Department of Veteran Affairs said it would immediately start work to bring the system to the market. However, a recently-published study has discovered that the AI system is not as effective when applied to females as compared to males. Another big problem is that simply modifying the system’s gender representation and sample size might not be enough to fix the algorithm. This possible problem in the initial study was acknowledged by the DeepMind and Veterans Affairs researchers. They noted that female patients made up less than 7% of the total patients in the study, and their model performance was very low compared to their male counterparts. However, it must be acknowledged that their findings only took into account patients suffering from early-stage kidney failure. These results were expanded upon in a more recent study of the deep learning AI led by a research team at the University of Michigan, which found that the model consistently misidentified female patients regardless of the severity of their acute kidney injury. The team also mentioned that when it added more women to the dataset, the performance discrepancies showed improvement among the general population. The problem persisted, however, when the AI was applied to a group consisting entirely of veterans, despite the enhanced controls for gender. This points to the fact that the problem isn’t solely the underrepresentation of women, according to the researchers; there are greater underlying issues at play. These might include practice patterns and the varying characteristics of female patients. About 1.7 million people per year lose their lives due to acute kidney injury, which is not easy to spot, and patients’ conditions often worsen before they receive potentially lifesaving treatment. A recent study found that 28% of those who develop the condition within the VA die within a year, with over 5% dying in the hospital. In the initial study of Google’s AI system, accurately predicted 90% of the patients in the VA whose kidney function eventually deteriorated to such an extent that they required dialysis. These sorts of results are typically considered breakthroughs in the medical AI space, but it’s often ignored how much more work lies ahead to ensure that the technology works well across different healthcare settings and on different kinds of patients. Jie Cao, the lead author of the study and a Ph.D. student at the University of Michigan, said, “We still have a long way to go in terms of using these models to change how health care works and to change a patient’s health.” She added that hasty adoption of Google's model might result in poor treatment choices by clinicians who might not be aware of its flaws. Google has announced new initiatives designed to speed up the company's AI research and development. The company’s researchers have released protocols and open-source code to implement whichever of its two models performs better. Furthermore, Google Cloud is providing a pilot-ready version of the model to healthcare systems worldwide that want to evaluate its potential benefits for their patients.

Technology & AI

Study Finds Google’s Kidney Disease AI to be Less Effective on Women

Editorial Team

December 7, 2022
3 min read

Elon Musk has revised the timeline for Neuralink’s brain implant, three years after introducing it and promising to start human trials by the end of 2020, a target that was covertly missed and forgone in favor of continuing animal studies. He predicted that by the middle of 2023, the business may finally begin implanting people, a year after its competitor Synchron. Musk stated, "We've been working hard to be prepared for our first person. I believe we’ve filed most of our documentation to the FDA, and we believe that in about six months we should be able to have our first Neuralink in person. We want to be very careful and confident that it will operate properly before putting our device in a human.” The CEO himself could be among the first to use the technology. He states that the device is discreet enough that people will not know if he has had it placed or not. To stimulate both mental and physical activity, the Neuralink implant is made to replace a removed portion of the skull by matching its size and thickness. Musk said it was similar to inserting an Apple Watch or Fitbit in a portion of the skull. According to the CEO, the company will prioritize the implant’s first two applications once it has the FDA's approval to start conducting human studies. The first application is focused on restoring vision to those who are visually impaired. Musk claims that the implant will be able to correct blindness in even those who were born blind. The second will be designed for those who are paralyzed and the aim is to restore movement. Plans for Neuralink include deploying numerous Neuralink implants in the brain and spinal cord to assist paraplegic individuals in regaining their ability to move and walk. Beyond its medical applications, Musk stated that the implant may assist all people to move closer to becoming half-human, half-robot hybrids, ideally with sufficient superintelligence to topple any potentially harmful artificial intelligence that may emerge to endanger mankind. Several claims had risen regarding the mistreatment of animals in testing. Musk reassured the audience that animal testing started only after the device had passed multiple testing phases on a sample artificial human brain, to which it was confirmed as a usable product. Neuralink’s brain implant has not shown success in animal trials as of yet and the claims made by the CEO are hypothetical at this point.

Technology & AI

Elon Musk believes Neuralink is six months away from human testing

Editorial Team

December 6, 2022
3 min read

mRNA Technology Successfully Tested for Universal Flue Vaccine researchers may be one step closer to creating the long-desired universal flu vaccine as a result of mRNA technologies. In a study published online in Science on November 24, researchers from the University of Pennsylvania's Perelman School of Medicine stated that they had created an mRNA-based vaccine that is effective against all 20 known variations of the A and B flu viruses. For the production of a successful seasonal flu vaccine, some foresight is required. There are numerous influenza viruses, but each vaccine can only target up to four of them. If scientists fail to correctly make predictions about different strains each season, that typically leads to a waste of a lot of time and money. Moreover, it puts the public at risk, as they stay unprotected from the flu. This is why the mRNA technologies at work here are in such high demand. Each year, experts forecast which four influenza viruses will cause the most damage during the coming season. On the basis of those strains, they create a "split virion protein vaccine," which involves growing the viruses in chicken eggs before cutting them up to render them inactive. These inactive fragments are then injected into the body, prompting the immune system to generate antibodies against the four different strains. The issue with this method is that it necessitates the development of new vaccines every year, some of which may prove inadequate against the season's main flu strains if initial predictions are inaccurate. The split virion protein vaccine can't protect against a wide range of strains because it can only handle up to four of them. Hence, scientists have tried developing universal vaccines targeting common parts of the flu virus, albeit without much success. In the Penn study, mRNA was used to generate an antibody response to Hemaglutinin (HA) proteins that protrude from the surface of the virus and enable it to infect host cells. The 20 subtypes of A and B influenza viruses that infect humans have their own unique HA proteins. Scientists tested the vaccine's efficacy by administering it to mice and ferrets and then exposing them to flu viruses representing 20 different lineages 28 days later. They discovered that while not all of the animals were completely immune to infection, they were protected from death or serious illness. Four months after receiving the vaccine, their antibody levels were still quite high. Additionally, the vaccine was effective in rodents that had already contracted the flu prior to vaccination. The vaccinated rodents developed antibodies against all 20 lineages, protecting them from lethal doses of influenza A, B, and C viruses. Scott Hensley, Ph.D., and senior author said in a press release, “The idea here is to have a vaccine that will give people a baseline of immune memory to diverse flu strains so that there will be far less disease and death when the next flu pandemic occurs.” The researchers are currently planning clinical trials in humans. They also want to include young children in the trials because they think the vaccine has the potential to create a long-lasting immune memory against all 20 flu variations.

Technology & AI

mRNA Technology Successfully Tested for Universal Flue Vaccine

Editorial Team

December 3, 2022
3 min read

Technology & AI

Study shows more accurate way for Aortic Dissections through AI

Editorial Team

November 30, 2022
3 min read