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Record W4406890538 · doi:10.1109/access.2025.3535677

Continuum and Soft Robots in Minimally Invasive Surgery: A Systematic Review

2025· review· en· W4406890538 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Access · 2025
Typereview
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsHotchkiss Brain InstituteUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsInvasive surgeryRobotComputer scienceArtificial intelligenceMedicineSurgery

Abstract

fetched live from OpenAlex

Faster recovery, reduced trauma, and improved patient outcomes drive innovations in minimally invasive surgery (MIS). Notwithstanding significant advancements, traditional MIS tools have been limited in navigating deep anatomical pathways and offering precise control at target sites. Continuum robotics has emerged as a solution, with recent developments enabling greater flexibility and maneuverability in surgical interventions. In this review, we first highlight recent developments in mechanical-continuum robots for traditional minimally invasive surgery and then summarize the current state-of-the-art in steerable catheter-based interventions. We discuss limitations to current approaches and explore the emerging potential of soft robots as a novel strategy to address the challenge of developing versatile, highly articulated flexible tools for minimally invasive surgical interventions. We hope that this review will, on the one hand, provide an introduction and resource for students and researchers alike, and on the other hand, will stimulate discussion vis-à-vis future directions in minimally invasive surgery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.328
Teacher spread0.284 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it