Evidence map›Paper›PMID 36590152›Full record

ReviewFrontiers in medical technology2022

Applications of artificial intelligence in orthopaedic surgery.

Faraz Farhadi, Matthew R Barnes, Harun R Sugito, Jessica M Sin, Eric R Henderson, Joshua J Levy

Abstract readReview
In one paragraph

Review in Frontiers in medical technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

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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

6 authors.

Faraz FarhadiGeisel School of Medicine, Dartmouth College, Hanover, NH, United States.
Matthew R BarnesGeisel School of Medicine, Dartmouth College, Hanover, NH, United States.
Harun R SugitoGeisel School of Medicine, Dartmouth College, Hanover, NH, United States.
Jessica M SinDepartment of Radiology, Dartmouth Health, Lebanon, United States.
Eric R HendersonDepartment of Orthopaedics, Dartmouth Health, Lebanon, United States.
Joshua J LevyDepartment of Pathology and Laboratory Medicine, Dartmouth Health, Lebanon, NH, United States.

Funding

Multimodal Fluorescence- and Imaging-Guided Surgical Navigation: Developing Methods for Subsurface, Indirect Visualization of Cancers Requiring Wide Local ExcisionK23EB026507 · NIBIB · DARTMOUTH-HITCHCOCK CLINIC · PI HENDERSON, ERIC R · 2018 to 2021
$679k
NIBIB NIH HHS K23 EB026507
6 · The paper itself

Abstract

The practice of medicine is rapidly transforming as a result of technological breakthroughs. Artificial intelligence (AI) systems are becoming more and more relevant in medicine and orthopaedic surgery as a result of the nearly exponential growth in computer processing power, cloud based computing, and development, and refining of medical-task specific software algorithms. Because of the extensive role of technologies such as medical imaging that bring high sensitivity, specificity, and positive/negative prognostic value to management of orthopaedic disorders, the field is particularly ripe for the application of machine-based integration of imaging studies, among other applications. Through this review, we seek to promote awareness in the orthopaedics community of the current accomplishments and projected uses of AI and ML as described in the literature. We summarize the current state of the art in the use of ML and AI in five key orthopaedic disciplines: joint reconstruction, spine, orthopaedic oncology, trauma, and sports medicine.

Indexed as

artificial intelligencedeep learningmachine learningOrthopaedicsOrthopaedic Surgery

Identifiers

PMID36590152
PMCPMC9797865

What OpenQuestion holds

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LicenceCC BY
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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.