This blog is based on the August 2023 market research report The Worldwide Market for In Vitro Diagnostic Tests, 16th Edition, now on sale from Kalorama Information
Artificial intelligence systems, which simulate human intelligence by learning, reasoning, and self-correction, have the potential to be more accurate than doctors at making diagnoses and performing surgical interventions. However, AI-based product developers maintain that machines will never replace doctors entirely, because the inter-relational quality of the doctor-patient relationship is vital and cannot be replicated.
Over the past several years, healthcare has witnessed a transformation with a shift from paper-based records systems to electronic records, and incorporation of digital health monitoring devices and other advanced patient screening systems. These advances have resulted in a data explosion, which can best be manipulated and analyzed using AI technology. The key driver of these AI implementations is to provide better care for patients, while reducing costs and administrative headaches and bottlenecks.
In support of AI, in January 2019, the Alliance for Artificial Intelligence in Healthcare (AAIH, /www.theaaih.org, Baltimore, MA) was formally launched following the inaugural meeting of its 22-person board of directors. The AAIH is a multi-stakeholder non-profit advocacy and education organization dedicated to promoting the further development and implementation of AI in healthcare. The membership-based alliance is a coalition of technology developers, pharmaceutical and device companies, research organizations and other associations engaged in advancing AI in the healthcare industry. The AAIH board and its committees will develop strategy and initiatives aimed at educating the public about the benefits and risks of AI, promoting investment in AI-related research and development, and working with government officials in the U.S., European Union and other jurisdictions to develop regulatory and technology standards.
AI continues to be challenging in healthcare; the following is an excerpt from The Journal of Robotics. Artificial Intelligence & Lawn- January-February 2020.
“Effective regulation of AI remains challenging due to several unique aspects of these technologies and their applications to healthcare. First, AI innovation is affecting a number of diverse segments of healthcare that face different regulatory risks. Innovators are looking to lend AI to areas such as clinical decision support, utilization review, reimbursement and payment, and research, among many others. This makes it difficult to establish a one-size-fits-all regulatory framework. Second, even within a specific segment of the industry, AI solutions are being created for an array of different purposes, which further frustrates creating a unified approach to regulation. Third, even if the absence of this variability, the definition of AI remains debated among experts and regulators. Without a common understanding about the attributes of these technologies that create risk, stakeholders will have difficulty determining what aspects of AI warrant regulation. Finally, many AI technologies are developed and operate as “black boxes” with opaque processes, often with the capacity to engage in unforeseeable actions. Without a robust understanding of how these technologies function, regulators will have difficulty developing guardrails for responsible development and use of AI.”
Some recent launches of artificial intelligence in healthcare include:
- Infermedica launched its AI-Driven Medical Guidance Platform with new modules and features
- Cornerstone launched its AI platform which includes automated software to accurately clean and prepare data for analysis in a short period of time
- Vital launched Care Adviser, a next-generation inpatient digital health solutions for hospitals
- Caption Health received CE marking for it Caption AI technology platform to improve heart ultrasound access using AI.
At the 2023 Association for Diagnostics & Laboratory Medicine (ADLM) [formerly AACC] meeting several areas were highlighted regarding the use of AI including personalized medicine, guiding clinical decisions in mass spectrometry, multiplexed genomic sequencing, applications of human brain organoid technology and building trust in healthcare as there is a healthy amount of skepticism.
AI in healthcare has huge and wide-reaching potential and the future of healthcare and the future of machine learning and artificial intelligence in medicine are deeply interconnected.