ArticleCureus2025
Transforming Surgery With Artificial Intelligence: An Early Analysis of Private Industry Trends.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Charting Tomorrow: A Practical Review of Artificial Intelligence in Medical Documentation.Plastic and reconstructive surgery. Global open · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe recent growth and integration of artificial intelligence (AI) into medical products have the potential to revolutionize surgical care. The private sector is largely responsible for this innovation. We aimed to characterize the growth, aims, and finances of private industry AI solutions within surgery.
methodsAn initial search using the CB Insights market intelligence platform returned 126 private companies; 20 met the exclusion criteria. Three independent reviewers extracted variables of interest, including company demographics, product classification, surgical subspecialty of interest, funding, valuation, and acquisition status. Product purpose and functionality were characterized in detail.
resultsThe first company was founded in 2003, with 50% (n=53) founded between 2015 and 2019. General surgery (n=57) and orthopedics (n=21) were the most common surgical subspecialties. The most common product categories were intraoperative image analysis (n=25), aiming to improve the visualization or navigation of the surgical site, and diagnostic imaging (n=18), aiming to improve the efficiency and accuracy of diagnosis and surgical planning. Of note, 12 companies aimed to increase the autonomy of surgical robotics. Finances were notably right-skewed, and total industry valuation exceeded one billion dollars, while six companies had been acquired.
conclusionsThere are numerous companies implementing AI solutions, and financial investment is high. Given the rapid pace of development, surgeon input is needed to reconcile product development with patient-centered care. Clinician participation in private industry development may address health inequities, shape the future role of surgeons in the operating room, and ensure safeguards with regulatory oversight and improved data reporting.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.