Evidence map›Paper›PMID 42254213›Full record

ReviewAnnals of medicine and surgery (2012)2026

Optimizing arthroplasty outcomes: the impact of artificial intelligence and robotic assistance.

Salar Baghbani, Yoosef Mehrabi, Fatemeh Boroumandfar, Amir Salimi, Erfan Babaeinejad, Mohammadamin Joshaghanian, Shayan Amiri, Mohammad Movahedinia, Mostafa Shahrezaee

Abstract readReview
In one paragraph

Review in Annals of medicine and surgery (2012), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Salar BaghbaniTrauma and Surgery Research Center, AJA University of Medical Sciences, Tehran, Iran.
Yoosef MehrabiTrauma and Surgery Research Center, AJA University of Medical Sciences, Tehran, Iran.
Fatemeh BoroumandfarOrthopedic Department, Kerman University of Medical Sciences, Kerman, Iran.ORCID https://orcid.org/0009-0000-0982-6763
Amir SalimiOrthopedic Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Erfan BabaeinejadDepartment of Orthopedic Surgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
Mohammadamin JoshaghanianOrthopedic Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shayan AmiriBone and Joint Reconstruction Research Center, Department of Orthopedics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Mohammad MovahediniaOrthopedic Department, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mostafa ShahrezaeeTrauma and Surgery Research Center, AJA University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotic-assisted surgery and artificial intelligence (AI) have revolutionized joint replacement surgeries by delivering superior precision in preoperative planning, real-time surgical navigation, and postoperative assessment capabilities. These advancements improve arthroplasty accuracy, reduce complication rates, and shorten recovery times. AI also supports the development of customized medical approaches that enhance surgery outcomes through patient-specific data analysis. Therefore, understanding the recent advancements in arthroplasty is essential for improving patient care. This comprehensive review explores how robotic systems and AI technologies enhance surgical precision and clinical decision-making. Although challenges and limitations remain, the upcoming years show potential for developing advanced medical solutions, which will enhance patient healthcare and surgical procedures.

Indexed as

AIarthroplastyrobotic surgerytotal joint replacement

Identifiers

PMID42254213
PMCPMC13236141

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.