Due to a shortage of radiologists and other imaging specialists, AI-enabled technologies are of significant interest—and hold particular promise—in medical imaging. In this article, Penny Pinnock of Siemens Financial Services (SFS), discusses the routes to investment available for healthcare organizations looking to acquire efficiency boosting technology while protecting their financial health.
Several alternatives exist to obtain FDA approval of artificial intelligence-enabled medical technology. Determining the best approach for a new device will require an awareness of each pathway’s specific requirements. An appreciation of the unique considerations for artificial intelligence-enabled technologies is another essential component of an efficient and effective application.
“Artificial Intelligence and Medical Products: How CBER, CDER, CDRH, and OCP are Working Together” outlines how FDA’s medical product centers plan to address regulation of AI used in medical products and their development.
A new survey from the Center for Connected Medicine at UPMC Sheds light on how healthcare systems are navigating both the promise and the possible risk of AI and generative AI.
Emerging technologies, integrated vendor ecosystems and enhanced regulatory compliance will redefine care delivery and shape the needs of healthcare stakeholders. Following are six healthcare technology trends that will shape care delivery and the MedTech market in 2024.
While AI is already making significant contributions to pre-operative planning and post-operative analysis, its utilization intra-operatively remains a key area for further development. Collecting and utilizing comprehensive intra-operative surgical data, as facilitated by innovative applications of existing technologies such as light field, will pave the way for advanced AI applications in spine surgery.
The integration of artificial intelligence (AI) into breast cancer detection and treatment is already making a profound impact. AI-powered algorithms enhance early detection by analyzing vast amounts of data and identifying subtle abnormalities often invisible to the human eye. These technologies empower healthcare professionals to make informed decisions, improving the accuracy of diagnoses and tailoring treatment plans to the specific genetic makeup and health conditions of individual patients. This integration represents a paradigm shift in the cancer care continuum.
“The V-CHAMPS Challenge showed us that artificial intelligence (AI) models that performed well on the synthetic patient data in Phase 1 also performed well on the RWD during Phase 2, highlighting the potential value of using synthetic data in AI model development.”
The National Institute of Standards and Technology (NIST) is seeking input from industry to support its response to President Biden’s Executive Order on AI. Comments, which are due February 2, 2024, will help NIST develop guidelines for evaluation and red-teaming, consensus-based standards and more.
Even AI models trained on general medical literature will have difficulty making sense of the nuances specific to primary care, which is full of unique jargon, abbreviations and other idiosyncrasies. As always, the proverbial devil is in the details. Any AI solution worth its salt must be fluent in the specific idioms of the field and empower clinicians to deliver the best care that they can.
