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Record W4401169429 · doi:10.7759/cureus.65868

The Role of Minimally Invasive Surgery in the Management of Inflammatory Bowel Disease: Current Trends and Future Directions

2024· review· en· W4401169429 on OpenAlexaff
S.B. Rathod, Nishant Ganesh Kumar, German D Matiz, S. Biju, Peter Girgis, Nagma Sabu, Hassan Mumtaz, Ali Haider

Bibliographic record

VenueCureus · 2024
Typereview
Languageen
FieldMedicine
TopicGastrointestinal disorders and treatments
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineInvasive surgeryLaparoscopyInflammatory bowel diseaseGeneral surgeryInflammatory Bowel DiseasesSurgeryLaparoscopic surgeryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Minimally invasive surgery (MIS) provides superior results in the surgical treatment of inflammatory bowel disease (IBD). There exist various minimally invasive procedures, each possessing its own set of benefits and drawbacks. This literature review outlines these methodologies and underscores their importance in enhancing the outcomes of patients with IBD. A grand total of 192 studies were carefully chosen and succinctly summarized. Conventional multiport laparoscopy is the most widely used MIS for IBD, with single-incision laparoscopy showing even better results. Robotic surgery offers comparable results but at higher costs and longer operation times. In the future, there will be widespread acceptance of single-incision laparoscopy and robotic surgery due to improved training and reduced expenses. Further research into the technology's utility in different IBD presentations could increase its usage.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.307
Teacher spread0.285 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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