Great choice for a scoping review topic! It's a rapidly evolving and crucial area.

Let's define your research question using the PCC framework, keeping the "scoping" nature in mind – which means you're aiming to map and characterize the existing literature rather than critically appraise intervention effectiveness.

PCC Framework Definition:

• P (Population): Who or what is the AI being applied to, or what is the focus of the diagnostic process?


• Initial thought: Patients, individuals, human subjects.


• Refinement for AI in Diagnosis: While ultimately for patients, the literature often focuses on the diagnostic tasks or diseases themselves, or the data used for diagnosis. To be broad for a scoping review, it can encompass various patient populations, diseases, or diagnostic scenarios.


• PCC Component: Individuals/patients (across diverse conditions, diseases, and demographic groups undergoing medical diagnostic processes)


• C (Concept): What is the core phenomenon, intervention, or area of interest?


• Initial thought: AI applications.


• Refinement: Be specific about what "AI" encompasses for this review, but also broad enough for scoping. This includes Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Expert Systems, etc., when applied to diagnosis. The "application" aspect means looking at how these technologies are used.


• PCC Component: Artificial Intelligence (AI) applications/technologies (including machine learning, deep learning, neural networks, natural language processing, computer vision, etc.)


• Co (Context): Where or in what setting is this phenomenon occurring?


• Initial thought: Medical diagnosis.


• Refinement: This includes all phases of the diagnostic process, across various medical specialties, clinical settings (hospitals, clinics, primary care), and even pre-clinical or research settings where diagnostic tools are developed.


• PCC Component: Medical diagnosis / Clinical diagnostic processes (across various medical specialties, clinical settings, and stages of disease detection or characterization)

Research Question using PCC:

Main Scoping Review Question:

"What is the nature, extent, and characteristics of Artificial Intelligence (AI) applications reported in the literature for medical diagnosis?"

Breaking Down the Main Question into Sub-Questions (to guide your review and data extraction):

To fully address the main question, your scoping review will likely explore several facets. These sub-questions directly link back to your PCC components and the "scoping" intent:

• P (Population / Focus of application): Which patient populations, diseases, or diagnostic tasks are AI applications primarily targeting in the literature?


• Examples: Diagnosing specific cancers, identifying neurological disorders from imaging, predicting sepsis, triaging emergency cases, interpreting pathology slides.


• C (Concept - Specifics of AI): What types of Artificial Intelligence (AI) technologies (e.g., machine learning algorithms, deep learning architectures, natural language processing models) are being utilized, and for what specific diagnostic functions (e.g., image analysis, risk prediction, text interpretation, biomarker discovery)?


• Co (Context - Settings & Outcomes/Characteristics): In which medical specialties or clinical settings are these AI applications being explored? What are the reported outcomes, performance metrics, and potential benefits or challenges associated with their use in diagnosis?


• Examples of outcomes/characteristics: Accuracy, sensitivity, specificity, efficiency, diagnostic speed, cost implications, ethical considerations, integration challenges, user acceptance.

This framework provides a clear and comprehensive scope for your review, allowing you to map the diverse landscape of AI in medical diagnosis effectively. Good luck!