On October 30, President Biden issued an Executive Order establishing new standards for artificial intelligence (AI). The order focuses on safety and security, privacy protections, advancement of equity and civil rights, promotion of innovation and competition and advancing American leadership in AI.
Genomics data scientist Harsha Rajasimha, Ph.D., Founder and Executive Chairman of IndoUSrare, highlights the risks of developing AI/ML algorithms based on biased data, as well as efforts underway to improve global collaboration on the collection and sharing of health data that may help us realize the potential of AI in diagnoses and treatment of rare diseases.
The COVID-19 pandemic pushed digital health to the forefront of care delivery, spurring massive innovation and investment. As the capital markets cool, investors are looking for companies with a proven return on investment, customer retention and good market fit.
AI not only improves data collection and analysis, it impacts which products are engaged in clinical trials, determines necessary medical criteria, helps design the trials and can even choose the best participating facilities. The result is, organizations that leverage AI will be more successful and will go to market faster than those that don’t.
For life sciences companies seeking to develop, deploy and successfully commercialize digital health products and solutions, the pathway to success can have many twists, turns and roadblocks. This article examines some of the major challenges to bringing digital health products to market and explores potential opportunities to ease the journey.
The FDA CDRH is seeking input from industry and the public on expanding access to home use medical technologies. The comment period closes on August 30, 2023.
Large sets of data are collected throughout the surgical continuum, but are chief medical officers and perioperative leaders able to use that data to drive clinical, operational, and financial improvements? Embracing data-driven surgery can help HCOs make use of their data to improve care, reduce costs and better manage staffing and workflow.
Market research and forecasting help ensure that you are investing in a device or drug that is needed and will be well received. In this article, Sanobar Syed, Associate Director of Forecasting, Market Insights and Strategies, BeiGene, highlights strategies to support data collection for forecasting in emerging markets.
This week Huma Therapeutics received FDA Class II 510(k) clearance for its Software as a Medical Device (SaMD) platform, potentially speeding approval of a variety of AI and machine-learning (ML)-powered digital health devices. We spoke with Kaushik Gune, U.S. Head of Healthcare at Huma, about the current state of digital health technologies, the value of partnerships to enhance the use of real world data and how digital health is likely to advance in the coming years.
Not all use cases are good candidates for machine learning. In this column we look at cases where AI/ML may be appropriate and when building a traditional algorithm to solve a problem is a better choice.
