The paper is rather speculative in places, but this is inherent in the nature of the topic, so is not necessarily a weakness. For the most part, the speculation is well-grounded in what is currently known and practised in both AI and medicine, and reads easily and fluently. While I’m not sure that the paper adds a great deal to our knowledge of the topic, it does provide a useful summary for those that are not entirely aware of AI in medicine and its implications.
Some issues to consider
- Overall, I would like to see a few concrete examples of where AI is currently being used in physiotherapy and physiotherapy education. (The last bullet point in my comments should also be noted, because, if the authors wish to argue that nothing is being done in the field, then they are opening themselves for a storm of criticism).
- “The field of AI research was first identified in the 1950s …..” Depending on how intelligence in machines is defined and described, this date could be set a hundred years earlier. I would not recommend that the authors use the expression “first identified” unless they are using it is a very particular way, and then they would need to define that way. A reference, anyway, is recommended, as “in the 1950s” is very vague, especially given that Alan Turing’s “Computing machinery and intelligence” was published in 1950. If this is the author’s reference, then it should be stated properly and cited.
- “…it has not lived up to the enthusiastic predictions of its supporters.” Again, this is far too vague. Many of the predictions did not have dates, and many of the predictions have occurred, so a blanket statement like could be easily challenged, and threaten the integrity of the paper.
- “the shelf life of a human education gets shorter” “shelf-life” might be considered a rather colloquial expression for an academic journal, and, perhaps, the authors can consider a more appropriate term.
- “Unfortunately, there is no evidence that any health professions programmes are even considering the incorporation of data science, deep learning, statistics, or behavioral science into the undergraduate curricula even though this is what is required to develop, evaluate, and apply algorithms in clinical practice” This is really far too broad. The authors simply cannot make such a blanket statement. At best, they can argue that they have not been able to find any evidence, or much evidence. But for that statement to have validity, the authors will have to give details of how they searched for that evidence, because the lack of evidence may be a failure to find, rather than a failure of existence. In fact, the statement is plain wrong, as it says that there are no health professions undergraduate curricula programmes that include statistics. That is just wrong.
So, a generally useful read, supplying some food for thought, but it can be strengthened, and some tidying up is required.