Jordan Levitt is a hands-on advisor to the offi cers of the company with an opendoor policy. A believer in deep collaboration and adhering to RACI concepts, Levitt is the tip of the innovation spear while also overseeing sourcing relationships to ensure the procurement of the highest grade data available, which ensures that transaction times are kept to a minimum. Wave HDC leverages the power of AI to secure the most accurate information available to companies throughout healthcare. Our proprietary Wave Analyzer technology coupled with our suite of tailored services and solutions autonomously verifi es, corrects and updates patient records in real-time. Wave HDC, Healthcare Data Curation, is a technology company focused on revenue cycle automation for the touchless capture of accurate demographic and insurance data.

Artificial intelligence (AI) is being embraced by hospitals and other healthcare organizations, which are using the technology to do everything from interpreting CT scans to predicting which patients are most likely to suffer debilitating falls while being treated. Electronic medical records are scoured and run through algorithms designed to help doctors pick the best cancer treatments based on the mutations in patients' tumors, for example, or to predict their likelihood to respond well to a treatment regimen based on past experiences of similar patients. But do algorithms, robots and machine learning cross ethical boundaries in healthcare? A group of physicians out of Stanford University contend that AI does raise ethical challenges that healthcare leaders must anticipate and deal with before they embrace this technology. "Remaining ignorant about the construction of machine-learning systems or allowing them to be constructed as black boxes could lead to ethically problematic outcomes," they wrote in an editorial published this week in the New England Journal of Medicine.

Then there is the ever-present pandemic that has been threatening this planet for years. It got me thinking: can technology be used to combat all these horrible diseases and improve patient outcomes. Is artificial intelligence going to play a role in this? We've achieved another milestone in Artificial Intelligence adoption: $6.9 Billion of market value and counting. The intelligent healthcare market will reach 67.4 Billion by 2027.

More than three in 10 healthcare leaders (38%) in Singapore are investing heavily in artificial intelligence in a bid to supercharge care in the city-state, the Philips Future Health Index 2022 report unveiled. Within the next three years, 74% of healthcare leaders expect AI to become a top investment area in the industry. Currently, healthcare leaders said their highest AI investment is for operational settings (16%), whilst only 12% invest in AI for clinical decision support which includes uses related to diagnosis or treatment recommendations, early warning scores, automatic disease detection and clinical decision guidelines. Others are investing in AI to integrate diagnostics (34%) and predict outcomes (32%). Whilst Singaporean healthcare leaders see AI as a key investment for the near future, many are already utilizing predictive analytics in some capacity, with almost half (45%) saying their hospitals or healthcare facilities have already adopted the technology.

Then there is the ever-present pandemic that has been threatening this planet for years. It got me thinking: can technology be used to combat all these horrible diseases and improve patient outcomes. Is artificial intelligence going to play a role in this? We've achieved another milestone in Artificial Intelligence adoption: $6.9 Billion of market value and counting. The intelligent healthcare market will reach 67.4 Billion by 2027. The future of AI in healthcare is bright but not peaceful.

The fundamental goals of healthcare are to improve people's lives and to prevent and treat disease. We may think of technology and artificial intelligence as tools for diagnostic and medical advancements like robotic surgery, "smart" prosthetics, or vaccine rollout. But the industry is discovering how the use of AI prevents healthcare fraud, waste and abuse (FWA), how advanced data security and cybersecurity solutions prevent security breaches, and how biometrics and machine learning protect patient information. Hospital directors are grappling with national losses of $300 billion to FWA each year and the constant threat of ransomware attacks, privacy breaches and identity theft. The massive scale of pandemic-related healthcare digitization increased these risks, causing healthcare leaders to seek better solutions.

In a survey of hundreds of healthcare decision-makers, Intel found that the percentage of respondents whose company is currently – or will be – using artificial intelligence nearly doubled after the onset of COVID-19. Among the predicted use cases for AI: early intervention analytics, clinical decision support and specialist collaboration. "Artificial intelligence in health and life sciences has greatly accelerated," said Stacey Shulman, vice president of the Internet of Things Group at Intel, in a blog post accompanying the findings. "From helping clinicians develop personalized protocols to streamlining clinical workloads or unlocking insights in genomics, infusing AI into these industries may be much closer than many initially thought," she said. Intel conducted an online survey of 200 senior decision-makers at healthcare organizations in April 2018, and then 230 in July 2020.

The healthcare world is currently under a tremendous amount of strain due to the COVID-19 pandemic. As a result, hospitals and providers are being forced to adopt new technologies to care for every patient. While the pandemic won't last forever, experts believe that these innovations will continue to impact the healthcare world in the future. One of the technologies leading the way is artificial intelligence (AI). A survey recently conducted by Intel found that 84 percent of U.S. healthcare leaders have already or plan to involve AI in their operations.

AIMed UK 2020 virtual summit took place early on. In the opening keynote session: Deployment of artificial intelligence (AI) in the UK and across the world, Professor Neil Sebire, Chief Research Information Officer at the Great Ormond Street Hospital for Children National Health Service (NHS) Foundation Trust talked about some of the considerations healthcare organization need to have as they plan to deploy AI tools at scale. Professor Sebire said healthcare organization ought to think about what is required, in terms of infrastructure, when it comes to dealing with healthcare data. Often, it's great to have talks focusing on electronic health records (EHRs) but these data warehouses do not facilitate utilization. What the healthcare system needs is a place which not only keeps all the data but also permits algorithm development; planning the deployment and scaling of AI, and everything else.

This article was written by Sergii Gorpynich, co-Founder and CTO at Star, co-written by Perry Simpson, Managing Director of Star, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. While it's easy to find healthcare AI use-cases online, it isn't clear which applications are viable, and which are hype. Healthcare leadership needs to consider the specific data assets, resources, and needs of their organizations before deciding on an AI initiative. In this article, we go into more detail about how executives need to adapt to the changes that AI might bring in businesses. Without a basic grounding in what AI can do and how it works, it can be impossible for executives to find and assess AI opportunity areas. Healthcare leaders should understand the basics of how technologies behind AI work, key concepts of machine learning and data science in general, the critical role of data, the importance of data infrastructure, and the kinds of problems that AI can and cannot solve.