Augmented intelligence (AI) promises to be a transformational force in health care, especially within primary care. Experts outline ways that innovations driven by AI--often called artificial intelligence--can aid rather than subvert the patient-physician relationship. "AI implemented poorly risks pushing humanity to the margins; done wisely, AI can free up physicians' cognitive and emotional space for patients, and shift the focus away from transactional tasks to personalized care," wrote the authors of an article published in the Journal of General Internal Medicine. The AMA is committed to helping physicians harness AI in ways that safely and effectively improve patient care. The authors--Steven Y. Lin, MD, and Megan R. Mahoney, MD, associate clinical professor of medicine and clinical professor of medicine, respectively, in the Division of Primary Care and Population Health at Stanford University School of Medicine, and AMA vice president of professional satisfaction Christine A. Sinsky, MD--reviewed promising AI inventions in 10 distinct problem areas.
These days, it might seem like algorithms are out-diagnosing doctors at every turn, identifying dangerous lesions and dodgy moles with the unerring consistency only a machine can muster. Just this month, Google generated a wave of headlines with a study showing that its AI systems can spot breast cancer in mammograms more accurately than doctors. But for many in health care, what studies like these demonstrate is not just the promise of AI, but also its potential threat. They say that for all of the obvious abilities of algorithms to crunch data, the subtle, judgment-based skills of nurses and doctors are not so easily digitized. And in some areas where tech companies are pushing medical AI, this technology could exacerbate existing problems.
Artificial Intelligence has made major strides in recent years. It has found application is different industrial verticals and businesses. It has revolutionized and revamped business processes and operations, which has resulted in increased efficiency and productivity. AI allows any particular digital device to easily observe as well as recognize a subject or object, deeply understand it and reply to different recognizable messages. Also, it can easily make decisions as well as learn to adapt its behaviour as well as the thinking process as it completely analyses the huge volume of data points.
Precision oncology firm Notable Labs is launching its first self-sponsored clinical trial, designed from the ground up to help validate its cancer patient matching platform over the long term. The observational study--which also represents the company's largest trial to date--aims to enroll up to 1,000 participants with a variety of blood cancers and will follow them for at least one year as they receive physician-led standard-of-care therapies at different sites across the U.S. and Canada. Separately, Notable's phenotypic and artificial intelligence-powered platform will be tested against multiple patient samples collected over time to provide a longitudinal view of its predictive value based on cancer mutations, drug responses and the outcomes of each participant. It will also search for patterns useful in the development of new treatments. The company combines AI approaches with automated lab processes to determine which drugs or combinations will be most effective for specific cancers.
I've always wondered if we could somehow use animals superior sense of vision to understand artificial neural networks better. Eagles have incredible spatial resolution, and understanding how they viewed adversarial samples might shed more light on the effect of spatial resolution for adversarial samples.
AI and Big Data in Cancer: From Innovation to Impact, a new conference from Elsevier, a global information and analytics business specializing in science and health, will bring together experts from all aspects of cancer research and the digital medicine value chain to understand how to translate artificial intelligence and data-driven innovations into new clinical care practices for patients. These leaders, including 2018 Nobel laureate for Medicine, Dr. James Allison, will share pragmatic insights on finding the right partners to move innovations successfully forward. "It is time to shift our conversation from'what-technology-can-do' to'what-medicine-needs' and to raise awareness of what else is necessary to translate an AI-enabled and data-driven innovation into a marketed product," said Dr. Lynda Chin, Conference Chair, Founder and CEO of Apricity Health and Professor at Dell Medical School at the University of Texas, USA. "Understanding what these hurdles are is the first step to overcoming them. "The aim of this conference is to bring innovators together with stakeholders, from patients, clinicians and developers to regulators, payers and investors, so they can network and identify collaborators who can help them accelerate the translation of their innovation into clinical practices," Dr. Chin said. "Insights from the program's 40 key opinion leaders will advance the emerging digital medicine industry, building bridges from computer to clinics," said Laura Colantoni, Vice President for Reference Content, Elsevier, and one of the main organizers for the conference. "We are particularly excited about establishing this conference as a venue for successful innovators, influential facilitators, regulators and payers, as well as investors to find, engage and collaborate with clinicians, researchers and patients to accelerate progress in this area.
The companies that are out there in the market, in order to serve their objectives better, need significant funding. In particular, for startups, fundraising is crucial to harness their rich potential to contribute to the growth of their respective industry and market. Without a funding source, a business, specially technology-business will flounder under the weight of its own debt. With the advancements in technology, the requirements, assets, and liabilities of such firms have grown exponentially in recent years. Amid this, funding works as a fuel on which a business runs and excels. When it comes to technologies like omnipresent AI or artificial intelligence, the pressure naturally increases to thrive in the market where big techs like Google, Microsoft, and significant others are operating.
Massive bushfires have destroyed millions of acres in Australia over the past few months. RAND's Melissa Finucane, a community resilience expert who grew up in a remote region of New South Wales, has watched in anguish. Experiences from previous disasters have highlighted concrete steps that can help communities start to recover right away, she says. She also notes that rural Australians have "a special kind of resilience," with perspectives and wisdom from years of hard experience. But still, measuring the effects that fires and other disasters have on people's mental health, social, and economic needs remains a unique challenge.
In recent times, we have seen an increasing number of instances of Artificial Intelligence (AI) donning the proverbial lab coat. In early 2019, thousands of people were screened every day in a hospital in Madurai by an AI system developed by Google that helps diagnose diabetic retinopathy, a condition that can lead to blindness. Startups like Niramai, based in Bengaluru are developing AI technology for early diagnosis of conditions like breast cancer and river blindness. The sudden, accelerated growth of Machine Learning not just in research but in all walks of life can bring to mind Black Mirror-esque visions of dystopia in which machines rule over humanity. But let us leave worrying about the consequences of the far future to science fiction and look at the immediate impact this technology has had in science.
A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.