Structured PREreview of AI Agents in Modern Healthcare: From Foundation to Pioneer -- A Comprehensive Review and Implementation Roadmap for Impact and Integration in Clinical Settings

Does the introduction explain the objective of the research presented in the preprint?

Yes

The introduction explains the importance of AI in healthcare by its market share, evolution/breakthroughs and the benefits of its clinical applications. It also explains the technical, implementation, and ethical challenges of AI in healthcare and solutions currently developed/tested to advance AI in healthcare. These paragraphs set the stage for the study's objective to classify AI agents in healthcare and introduce an implementation roadmap that guide clinicians and IT professionals in scaling up AI in healthcare using a graduated/modular approach.

Are the methods well-suited for this research?

Somewhat appropriate

Although the research study conducts a systematic review using the PRISMA framework, key steps of the framework (tied to PRIMSA goals of transparency and comparability) are missing in the methods section. For example, authors do not include the PRIMSA flow chart or an evaluation of risk of bias.

Are the conclusions supported by the data?

Highly supported

Authors conclusions are supported by a thorough presentation of their conceptual framework/results alongside several visuals and examples that comprehensively tackles the study objective.

Are the data presentations, including visualizations, well-suited to represent the data?

Somewhat appropriate and clear

Visuals presented are easy to comprehend/interpret but additional visuals are needed to thoroughly capture the PRIMSA method and consistently differentiate AI agent classifications by modular AI architecture/subsystems. For example, figure 7 does not clearly show how the agent human interaction framework differentiates foundation, assistant, partner/pioneer AI agents and the purpose of the colors in the figure is unclear.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Very clearly

Authors thoroughly discuss and interpret their findings using a conceptual framework and implementation roadmap. They also thoroughly explain next steps; technical, ethical and implementation challenges as well as opportunities that can be leveraged to be achieve next steps.

Is the preprint likely to advance academic knowledge?

Highly likely

This preprint advances academic knowledge by furthering understanding of AI agents in healthcare. Previous publications classify AI agents in healthcare by function and architecture while this article classifies/explains AI agents by autonomy and its evolution over time.

Would it benefit from language editing?

No

Would you recommend this preprint to others?

Yes, it’s of high quality

Is it ready for attention from an editor, publisher or broader audience?

Yes, after minor changes

1. Authors should consider including a PRIMSA flowchart 2. Author should consider addressing overlap in modular architecture, clinical applications, implementation challenges for partner and pioneer AI agents or clearly identify factors that differentiate these two classes of AI agents 3. Authors should consider having all visuals of modular subsystems/architecture (e.g. perception, memory/learning, interaction/conversational modules) capture differences in AI agent classifications discussed in the narrative. 4. Author should consider using typical manuscript section headers (e.g. Results and Discussion) to improve readability

Competing interests

The author declares that they have no competing interests.