Machine learning algorithms have reached a familiar milestone in the healthcare industry --in order for them to be more widely embraced by providers, different approaches to roadtesting and validating them are underway.
GSK is making greater use of artificial intelligence and computational techniques as part of its drug discovery efforts. Speaking during the HLTH conference in Las Vegas, executive Mike Montello likened his company's techniques to the efforts to study and analyze images from outer space.
As technology advances, AI-powered tools will increasingly reduce the administrative burdens on healthcare providers.
Alviss.ai CEO and Founder Dr. Pavel Overtchouk talks about how the company’s stroke prediction software seeks to be the first attempt to apply predictive medicine to cardiovascular interventions and heart surgery.
Mount Sinai researchers published a study that could improve neuroscientists’ understanding of the progression of Alzheimer’s and other forms of cognitive decline. It proved that white matter may be a more important region to look at than was previously thought.
As part of its Envision U.S. Healthcare Summit, Microsoft conducted interviews with executives at Aetna CVS Health and Humana to highlight some of the ways these companies are adapting to consumerization of healthcare.
Health systems are seeing increased operational efficiency after applying machine learning analytics to their operating room block scheduling. Given the multitude of challenges health systems face — from increased labor costs to material shortages to reimbursement woes — some health system digital executives say it’s critical that hospitals incorporate machine learning into their block schedules sooner rather than later.
Closing cancer health equity gaps require medical breakthroughs made possible by new funding approaches.
Pharma companies already rely heavily on data and predictive analytics to assess new drugs. In the same way, analytics can be used to enhance legal advice and improve litigation strategies.
The goal of implementing artificial intelligence and machine learning in clinical research is not to replace humans with digital tools but to increase their productivity.
The voice solution Suki Assistant uses machine learning and natural language processing to accurately understand and document information and respond to physician commands, according to the company.
To avoid the “trends trap” of heightening the health tech disconnect in the wake of innovation, we must consider how best to proceed in investing and building new technologies that enable long-term transformation of care delivery, not just this year’s trends.
The future looks bright for the integrated specialty pharmacy model – for health systems, providers, and most importantly, for patients.
As we near two years since Covid-19 first struck the U.S., our healthcare system continues to grapple with staffing shortages, sicker patients, and an aging population, leading to an overburdened workforce. Luckily, there are technologies – such as machine learning algorithms (MLAs) and artificial intelligence – that continue to evolve and support care teams in […]
The life sciences industry is more quickly adapting to new methods, standards and requirements. The focus is now on how to drive greater data governance and quality through a unified framework. The challenge comes in instituting a framework that will meet regulatory and labeling requirements.
Learn how healthcare organizations are working with Microsoft to enhance patient engagement, accelerate healthcare innovation, support collaboration, improve clinical and operational insights and transform healthcare in the cloud.
Beth Hoffman, Origami Therapeutics CEO, talks about how the company's platform enables the discovery and development of protein degraders and conformation correctors to match the best drug to treat neurodegenerative diseases, such as Huntington's disease.
Microsoft seeks to change the way pharma industry companies use technology to navigate human resource challenges and restore confidence in drug development supply chains.