2020
DOI: 10.1159/000511351
|View full text |Cite
|
Sign up to set email alerts
|

Artificial Intelligence-Assisted Surgery: Potential and Challenges

Abstract: <b><i>Background:</i></b> Artificial intelligence (AI) has recently achieved considerable success in different domains including medical applications. Although current advances are expected to impact surgery, up until now AI has not been able to leverage its full potential due to several challenges that are specific to that field. <b><i>Summary:</i></b> This review summarizes data-driven methods and technologies needed as a prerequisite for different AI-based ass… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
23
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
4
1

Relationship

1
8

Authors

Journals

citations
Cited by 41 publications
(23 citation statements)
references
References 40 publications
0
23
0
Order By: Relevance
“…Multiple studies have briefly touched on some of the difficulties of implementing AI in procedural specialties and practices. 10,13,17,20,39,40 Here, we break down the most significant of these challenges in the following categories: inherent specialty challenges, regulatory challenges, intellectual property, raising capital, and ethical challenges.…”
Section: Challenges Of Implementing Artificial Intelligencementioning
confidence: 99%
See 1 more Smart Citation
“…Multiple studies have briefly touched on some of the difficulties of implementing AI in procedural specialties and practices. 10,13,17,20,39,40 Here, we break down the most significant of these challenges in the following categories: inherent specialty challenges, regulatory challenges, intellectual property, raising capital, and ethical challenges.…”
Section: Challenges Of Implementing Artificial Intelligencementioning
confidence: 99%
“…[4][5][6][7] Many startup companies have been established in this space, with further involvement of larger, well-known tech companies that acquire these startups or establish their own capabilities. 8 However, while multiple studies have pointed out the great potential AI and ML have for procedural medical specialties such as interventional radiology (IR), [9][10][11][12][13][14] to date practical applications of ML in IR have not been introduced to clinical practice. In fact, in a recent article by van Leeuwen et al reviewing 100 commercially available AI products in radiology, there is a notable absence of IR in the listed applications.…”
mentioning
confidence: 99%
“…The heterogeneous sensors in the OR are known as “context-aware assistance” and help in the smooth functioning of the surgical procedures[ 56 ]. ML and data annotation can be used to identify the phases of surgery and apply them to identify any deviation or delay in surgical steps[ 57 ]. Surgical navigation technology or computer-assisted abdominal surgery use preoperative or intraoperative imaging to track surgical instruments and help to describe hidden surgical anatomy.…”
Section: Intraoperative Managementmentioning
confidence: 99%
“…The availability of realistic, synthetic data is especially crucial in the field of computer-assisted surgery (CAS) [24,5]. CAS aims at providing assistance to the surgical team (e.g.…”
Section: Introductionmentioning
confidence: 99%