Entrepreneur, business magnate and billionaire Elon Musk believes Neuralink's sophisticated implantable brain-machine interfaces and not Mark Zuckerberg's VR-driven metaverse could soon put humans "fully into virtual reality." Neuralink co-founder Musk took a dig at Zuckerberg and other proponents of virtual reality and metaverse in an interview with the conservative and Christian satire site Babylon Tree on Tuesday. During the interview, the billionaire revealed his lack of support for the metaverse and Web3, two trends believed to radically change the tech world. For the Time Magazine's 2021 Person of the Year, his neurotechnology company, Neuralink, is more capable of providing a better environment for people to fully immerse in virtual reality. "In the long term, a sophisticated Neuralink could put you fully into virtual reality," Musk noted.

When legal regulations get ahead of technological developments, the progress of human society may be constrained. When technological developments run ahead of legal regulations, the unregulated new technologies may harm instead of benefit human society, defying technological development's fundamental purpose. This is exactly what has happened in our world in the past decade, as technological developments far outpaced legal regulations. Worse, traditional legal frameworks focus on the relation between people, whereas we must develop a legal framework to regulate relations between people and intelligent machines in the current era. Integrating AI technologies into human society imposes unique legal challenges without any precedence.

Artificial intelligence (AI) models that evaluate medical images have potential to speed up and improve accuracy of cancer diagnoses, but they may also be vulnerable to cyberattacks. In a new study, University of Pittsburgh researchers simulated an attack that falsified mammogram images, fooling both an AI breast cancer diagnosis model and human breast imaging radiologist experts. The study, published today in Nature Communications, brings attention to a potential safety issue for medical AI known as "adversarial attacks," which seek to alter images or other inputs to make models arrive at incorrect conclusions. "What we want to show with this study is that this type of attack is possible, and it could lead AI models to make the wrong diagnosis -- which is a big patient safety issue," said senior author Shandong Wu, Ph.D., associate professor of radiology, biomedical informatics and bioengineering at Pitt. "By understanding how AI models behave under adversarial attacks in medical contexts, we can start thinking about ways to make these models safer and more robust." AI-based image recognition technology for cancer detection has advanced rapidly in recent years, and several breast cancer models have U.S. Food and Drug Administration (FDA) approval.

Researchers led by a scholar from City University of Hong Kong (CityU) have developed a novel artificial intelligence (AI) framework to make predictions on potential synergistic anti-cancer drug combinations for both therapeutic and toxic effects. Many of the biotech sector's biggest wins of late have come through drug combinations, utilizing the strengths and downplaying the weaknesses of available therapies, including recent developments from Oncolytics Biotech Inc. Merck, Amgen Inc., Bristol-Myers Squibb Company, and Mirati Therapeutics, Inc. For example, significant work is being done on behalf of women in America, where breast cancer is known to be the second leading cause of death from cancer--with an estimated 42,000 deaths in the US in 2020. The problem also persists in China, where breast cancer is now estimated to be the largest subtype of cancer among women, with over 416,000 cases and over 117,000 deaths in 2020. As part of the fight against breast cancer, a multinational front is moving forward between US-based Oncolytics Biotech Inc. and Chinese multinational clinical-stage biopharma developers Adlai Nortye.

Elon Musk claims his Neuralink, a brain-interface technology company, is less than a year away from implanting chips into human brains. The news comes from the billionaire himself during a live-streamed interview with The Wall Street Journal CEO Council Summit on Monday, when asked about plans for the company in 2022. 'Neuralink's working well in monkeys and we're actually doing just a lot of testing and just confirming that it's very safe and reliable and the Neuralink device can be removed safely,' Musk said. 'We hope to have this in our first humans -- which will be people that have severe spinal cord injuries like tetraplegics, quadriplegics -- next year, pending FDA approval. 'I think we have a chance of being able to allow someone who cannot walk or use their arms be able to walk again – but not naturally.'

Elon Musk has said he does not want to "raise hopes unreasonably" but is "increasingly confident" his brain-machine interface startup Neuralink will have its first implant devices in humans by 2022. The billionaire said he is "cautiously optimistic" the implants can restore full-body functionality for tetraplegics and quadriplegics, adding that the company's standards for implanting the brain-computer interface device are higher than what the FDA requires. "I think we have a chance with Neuralink to restore full-body functionality to someone who has a spinal cord injury," Musk said in a video interview during the Wall Street Journal's CEO Council Conference. "I don't want to raise hopes unreasonably, but I'm increasingly convinced that this could be done," he added. Crypto market enters'extreme fear' following bitcoin crash – follow live France to mimic Elon Musk with own SpaceX-style launcher Suicide machine that kills users in the blink of an eye'legalised in Switzerland' Suicide machine that kills users in the blink of an eye'legalised in Switzerland' In April, the startup released a video of a monkey named Pager with the brain-computer interface chip that was able to play video games using only its mind.

Since 2018, Health Canada has undertaken an initiative to adapt its regulatory approach to better support digital health technologies, specifically medical devices. Key focus areas include artificial intelligence, software as a medical device, cybersecurity, medical device interoperability, wireless medical devices, mobile medical apps and telemedicine. To meet this goal, Health Canada established the Digital Health Division under the Medical Devices Bureau and has been increasing its efforts to build in-house expertise. On October 27, 2021, Health Canada, the US Food and Drug Administration (FDA), and the United Kingdom's Medicines and Healthcare Products Regulatory Agency (MHRA) jointly published the Good Machine Learning Practice for Medical Device Development: Guiding Principles. The document consists of 10 guiding principles to help promote safe, effective, and high-quality use of artificial intelligence and machine learning (AI/ML) in medical devices.

The forecasting tool assesses multiple patient-specific biological and clinical factors to predict the degree of response to immune checkpoint inhibitors and survival outcomes. It markedly outperforms individual biomarkers or other combinations of variables developed so far, according to findings published in Nature Biotechnology. With further validation, the tool may help oncologists better identify patients most likely to benefit from ICB. Discerning, prior to treatment, patients for whom ICB would be ineffective could reduce unnecessary expense and exposure to potential side effects. It could also indicate the need to pursue alternate treatment strategies, such as combination therapies. "It's important to know which treatment modalities patients are most suited for," said Dr. Chan, director of Cleveland Clinic's Center for Immunotherapy & Precision Immuno-Oncology.

The Food and Drug Administration recently sought comments on the role of transparency for artificial intelligence and machine learning-enabled medical devices. The FDA invited comments in follow up to a recent workshop on the topic. The workshop was part of a series of efforts the FDA has had in this space. These include its Digital Health Center of Excellence and a five-part Action Plan for AI and machine-learning enabled medical devices. As part of the action plan, the FDA indicated it wants to issue guidance on software learning over time and help the industry be "patient-centered."

The Food and Drug Administration recently sought comments on the role of transparency for artificial intelligence AI and machine learning-enabled …