From personalized medicine to CRISPR gene editing, AI has a revolutionary part to play in tackling some of the longest-standing ills and ailments facing humanity. To celebrate the launch of our new issue, 'A New Era In Healthcare', we've compiled some of the latest cutting-edge research, statistics, and reports from the world's leading health, pharma, and tech giants, including: We'll be exploring the big questions surrounding the future of human healthcare and provision; the crises facing health services around the world due to an aging population; the use cases for AI that are already leading to transformative changes in pharma, medicine, and care; and the next big steps for the nurses, doctors, surgeons, and physicians who keep the whole world healthy. In the next 3 weeks, expect to read features about AI and the future of the National Health Service on its 70th birthday; guest articles from leading figures in AI and health, such as Kerrie Holley, Technology Fellow at Optum; interviews with some of the most groundbreaking start-ups in the field; as well as real-world insights into revolutionary technologies such as genomics and AI social care. In the meantime, stay tuned for all of our latest news, features, interviews, videos, and more on aibusiness.com. DISCLAIMER: CC BY-NC-ND – You are free to share, copy, and redistribute the material in any medium or format for non-commercial purposes but you must give appropriate credit to aibusiness.com and indicate if any changes have been made.
A new smartphone app aims to connect medical marijuana patients with advice on getting the most of their prescription, through a growing database of knowledge fed by artificial intelligence. The CannaBot is being announced Friday by the suburban Philadelphia biotechnology and pharmaceutical company Affinity Bio Partners, said CEO Christina DiArcangelo Puller. The system starts out with a medical cannabis dispensary or prescribing physician signing up to use CannaBot. Then, their patients would access it through an Amazon Alexa or Google Home smart speaker. Say they've been taking a certain dosage of the cannabis compound CBD for a headache, but the pain won't go away; they could direct the speaker to bring up CannaBot then ask: What should I do?
The applications of artificial intelligence (AI) in healthcare are countless. For many pharmaceutical companies, machine learning is the most important aspect of AI, with the potential to allow machines to ultimately surpass the intelligence levels of humans. The success of AI in drug discovery is largely due to hardcore Research & Development in learning section of brain sciences, a field of machine learning that is built using artificial neural networks that model the way neurons in the human brain talk to each other. This technology can turn bots into dynamically agile than the human beings. The type of artificial intelligence (AI) which scares some of the greatest minds, like Elon Musk and Stephen Hawking, is called "general artificial intelligence" -- the one which can "think" pretty much like humans do, and which can quickly evolve into a dangerous "superintelligence".
Nevshehir writes: "Digital medicine is currently tracking down and destroying mutant cancer cells faster than ever before." If there was ever an industry in dire need of increased efficiency, cost containment and improved outcomes, health care tops the list. Despite consuming 18 percent of our nation's GDP--equal to $3.4 trillion in annual expenditures--it is responsible for nearly 250,000 deaths due to medical errors, poor record keeping and a dismal lack of shared data among doctors about patients in their care. From blockchain technology to surgical robots, medical experts worldwide agree that big data and artificial intelligence (AI) will play a key role in vastly improving health care quality and delivery. Aided by advances in sensor capabilities, computational power and algorithmic ingenuity, the pace of medical innovation is accelerating rapidly.
Wolters Kluwer was well received at the IEEE conference, International Conference on Healthcare Informatics (ICHI), in NYC on June 4, 2018. ICHI is a leading conference in Healthcare Informatics space bringing together academia and industry research using Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Natural Language Processing (NLP). Among the main highlights, I was the invited speaker to present the cutting-edge research by Wolters Kluwer Health and Global Platform Organization (GPO) on discovering and providing actionable information to clinicians from the data explosion coming from EMR, Payer, Drugs safety and efficacy, Wolters Kluwer applications, among others. Our vision uses AI to augment doctors, nurses, and others to navigate intelligently through the growing volume, velocity, and variety of the healthcare information they encounter daily. It was a great opportunity to speak at the IEEE platform and represent Wolters Kluwer.
New York (GenomeWeb) – Researchers from Princeton University and the Flatiron Institute's Center for Computational Biology have developed a deep learning approach that they say can predict the effects of genetic variants in noncoding regions on gene expression in specific tissues as well as on disease risk.
Duchenne Muscular Dystrophy (DMD) is a rare muscle disorder affecting children that results in loss of the ability to walk. It's rapidly progressive -- average life expectancy is about 20 years -- and caused by genetic mutations on the X chromosome that regulates the production of dystrophin, a protein thought to play a role in maintaining muscle cell membranes. For DMD sufferers and other patients with rare degenerative diseases, there's now hope on the horizon. Insilico Medicine and A2A Pharmaceuticals today launched Consortium.AI, a new venture founded with the goal of applying advances in artificial intelligence (AI) to cutting-edge drug discovery. Through Consortium.AI, the two companies will collaboratively develop therapeutic treatments for DMD and other severe genetic disorders and use machine learning to validate the most promising candidates.
The hype of Artificial Intelligence is towering to reach the global market value of approximately 7,35 billion US dollars in 2018 and expected to generate 89,85 billion US dollars in 2025. The penetration of this cognitive function has almost knuckled every industry. However, AI is known narrow in executing the tasks that don't require insightful research. The healthcare's adoption of Artificial Intelligence is expected to outstretch all other relevant industries. Healthcare Industry is one of the largest industry with massive patient's database.
Artificial Intelligence (AI) has massive potential for future applications. Looking at the pace with which AI is entering different areas of our life, it is definite to say that soon it is going to be present all over the place, and there's nothing to worry about that! For those cautious of a robotic evolution shouldn't fear anything – the arrival of AI into the healthcare industry is more about the expansion, sharpening, and easing the minds of the physician so that the doctors can do the same to their patients. From intense symptomatic calculations to finely-tuned careful robots, the innovation is making its essence known across medical verticals. Unmistakably, AI has a place in the pharmaceutical industry – what we don't know yet is its worth.
Digital technologies can transform how companies approach clinical development by incorporating valuable insights from multiple sources of data, radically improving the patient experience, enhancing clinical trial productivity, and increasing the amount and quality of data collected in trials. But where is the industry in adopting these transformative technologies? We interviewed 43 leaders across the clinical development ecosystem to understand the current level of adoption of digital technologies and how it can be accelerated. We found that the industry has been slow to digitize its clinical development processes, and that digital adoption varies widely. Even the most advanced organizations are simply piloting several technologies in different areas of clinical development, focusing on piecemeal solutions or new tools to support the existing process. Our research and client experience suggest that digital transformation is a complex, resource-intensive, and lengthy undertaking. But the rewards can be significant: Early adopters can benefit from better access to and engagement with patients, deeper insights, and faster cycle times for products in development. Many in our study expressed a desire to be fast followers, but given the complexity of operationalizing a digital strategy, the reality is that undue delay could put organizations at a competitive disadvantage. At the same time, our research also indicates that biopharma companies and contract research organizations (CROs) will need to overcome several challenges to realize the potential of digital in clinical development: immature data infrastructure and analytics, regulatory considerations, and internal organizational and cultural barriers. Biopharma companies should consider building updated data infrastructure and governance, engaging early with regulators to discuss new technologies, and developing a measured approach to evaluating and implementing technologies within their organizations. CROs can enable this change by advancing interoperable digital platforms and vetting promising technology applications. Cross-industry consortia could help advance the industry as a whole by offering a forum to share early successes and supporting the development of standards. The time to act is now.