Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities

Clinical artificial intelligence (AI) is a novel technology, and few economic evaluations have focused on it to date. Before its wider implementation, it is important to highlight the aspects of AI that challenge traditional health technology assessment methods.

At least a decade ago IBM developed an early AI application to be used by the M.D. Anderson Medical Group. It was intended to assist oncologists by matching anti-cancer therapeutics. with the appropriate cancers.  Their efforts were frustrating, and challenging to all concerned. In a clinical setting the M.D. Anderson oncology doctors terminated the experiment.  The data base was inadequate, and physicians did not know how to use it for clinical work.  It was inefficient and much time was devoted to learning how it worked.  The project was abandoned.  It remained an experiment and was not mature enough to begin a formal clinical trial. 

The FDA (Food and Drug Administration) uses a well organized methodology of Phase I, II, and III  successful testing prior to approval for marketing for clinical use. The routine applies to medical devices as well as pharmaceuticals.  Even after approval for marketing the FDA follows closely to monitor for unexpected adverse events.

Advances in Artificial Intelligence in Medicine.

Artificially intelligent computer systems are used extensively in medical sciences. Common applications include diagnosing patients, end-to-end drug discovery and development, improving communication between physician and patient, transcribing medical documents, such as prescriptions, and remotely treating patients.

What is the future of AI in medicine?

AI can add value by either automating or augmenting the work of clinicians and staff. Many repetitive tasks will become fully automated, and we can also use AI as a tool to help health professionals perform better at their jobs and improve outcomes for patients.

 What are the pros and cons of artificial intelligence in healthcare?

The link goes into great detail about the pros and cons of AI in healthcare

References: (peer reviewed from Scientific Journals)

Artificial Intelligence, or Machine Learning uses algorithms controlled by codes. The unique part of AI is that it learns from the data it is given.  A.I. requires huge amounts of data to develop a semblance of what we call intelligence.

A.I. has arrived in our lives

Machine learning is creeping into communications, and business practices surreptitiously. At times we cannot discern if we interface with a human or an AI such as a. chatbot or a telephone answering tree.  The Turing Test is a measure of the utility of AI.

Assessing the Economic Value of Clinical Artificial Intelligence: Challenges and Opportunities - ScienceDirect