Transforming Surgical Training With AI Techniques for Training, Assessment, and Evaluation: Scoping Review

4/10 importance · ai assisted · surgical training · 2025 · validator confidence 70% · research

The problem

Surgical training assessment and evaluation rely on traditional methods that may be improved by data-driven AI techniques.

Why it matters

Quality of surgical skill assessment directly affects trainee competence and patient safety.

What the AI did

A PRISMA-ScR scoping review of studies (2020–2024) examining how AI algorithms, predictive analytics and data-driven insights enhance surgical trainees' learning paths and performance evaluation.

Results

not stated in source

Impact

Review identifies current AI applications and research gaps; no measured outcome stated.

How important is this problem?

4/10 — real but narrower advance

Surgical skill assessment affects trainee competence and patient safety, but abstract gives no scale or outcomes; a scoping review of 56 studies mapping applications and gaps.

inferred — an explicit judgement from the source text.

Scale stated in source: not stated in source

Ratings use a published rubric and are AI-assisted, not measured or peer-reviewed. Method

Sources & verification

Primary source: https://doi.org/10.2196/58966
Model / method: not stated in source
Organization: not stated in source
Validator notes: glm-5.3: ok (confidence 70) | Authentic scoping review; abstract states no concrete results.
Keywords: surgical training, AI assessment, scoping review, predictive analytics, medical education

A second-stage review judged this entry against the primary source; status “verified”. “Verified” means the evidence supported the claim — it does not mean the underlying result was independently reproduced.

Multimodal deep learning of fundus abnormalities and traditional risk factors for cardiovascular risk prediction
Cardiovascular disease, the leading global cause of death, needed better risk identification from accessible data.

Medicine & Health · 2023 · ai assisted · 10/10 importance
Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualization
Detecting tuberculosis accurately and early from chest X-ray images, since late diagnosis can be life-threatening.

Medicine & Health · 2020 · ai assisted · 10/10 importance
A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach
Accurate early prediction of stroke is needed to enable timely treatment, but medical data is imbalanced.

Medicine & Health · 2022 · partially solved · 10/10 importance
Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning
Cardiovascular disease often goes undiagnosed until serious events; non-invasive diagnosis from retinal images and DXA scans was lacking in Qatar.

Medicine & Health · 2022 · partially solved · 10/10 importance
Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential
Predicting and managing COVID-19 disease severity was difficult, and mechanisms underlying severity were unclear.

Medicine & Health · 2021 · partially solved · 10/10 importance