Literature DB >> 35902390

Artificial intelligence in spine surgery.

Ahmed Benzakour1, Pavlos Altsitzioglou2, Jean Michel Lemée3, Alaaeldin Ahmad4, Andreas F Mavrogenis5, Thami Benzakour6.   

Abstract

The continuous progress of research and clinical trials has offered a wide variety of information concerning the spine and the treatment of the different spinal pathologies that may occur. Planning the best therapy for each patient could be a very difficult and challenging task as it often requires thorough processing of the patient's history and individual characteristics by the clinician. Clinicians and researchers also face problems when it comes to data availability due to patients' personal information protection policies. Artificial intelligence refers to the reproduction of human intelligence via special programs and computers that are trained in a way that simulates human cognitive functions. Artificial intelligence implementations to daily clinical practice such as surgical robots that facilitate spine surgery and reduce radiation dosage to medical staff, special algorithms that can predict the possible outcomes of conservative versus surgical treatment in patients with low back pain and disk herniations, and systems that create artificial populations with great resemblance and similar characteristics to real patients are considered to be a novel breakthrough in modern medicine. To enhance the body of the related literature and inform the readers on the clinical applications of artificial intelligence, we performed this review to discuss the contribution of artificial intelligence in spine surgery and pathology.
© 2022. The Author(s) under exclusive licence to SICOT aisbl.

Entities:  

Keywords:  Artificial intelligence; Machine learning; Spine; Surgery; Surgical robots

Year:  2022        PMID: 35902390     DOI: 10.1007/s00264-022-05517-8

Source DB:  PubMed          Journal:  Int Orthop        ISSN: 0341-2695            Impact factor:   3.479


  76 in total

1.  Clinical accuracy of computer-assisted two-dimensional fluoroscopy for the percutaneous placement of lumbosacral pedicle screws.

Authors:  Bheeshma Ravi; Ali Zahrai; Raja Rampersaud
Journal:  Spine (Phila Pa 1976)       Date:  2011-01-01       Impact factor: 3.468

2.  Clinical acceptance and accuracy assessment of spinal implants guided with SpineAssist surgical robot: retrospective study.

Authors:  Dennis P Devito; Leon Kaplan; Rupert Dietl; Michael Pfeiffer; Dale Horne; Boris Silberstein; Mitchell Hardenbrook; George Kiriyanthan; Yair Barzilay; Alexander Bruskin; Dieter Sackerer; Vitali Alexandrovsky; Carsten Stüer; Ralf Burger; Johannes Maeurer; Gordon D Donald; Donald G Gordon; Robert Schoenmayr; Alon Friedlander; Nachshon Knoller; Kirsten Schmieder; Ioannis Pechlivanis; In-Se Kim; Bernhard Meyer; Moshe Shoham
Journal:  Spine (Phila Pa 1976)       Date:  2010-11-15       Impact factor: 3.468

3.  Pedicle screw placement accuracy: a meta-analysis.

Authors:  Victor Kosmopoulos; Constantin Schizas
Journal:  Spine (Phila Pa 1976)       Date:  2007-02-01       Impact factor: 3.468

Review 4.  The accuracy of pedicle screw placement using intraoperative image guidance systems.

Authors:  Alexander Mason; Renee Paulsen; Jason M Babuska; Sharad Rajpal; Sigita Burneikiene; E Lee Nelson; Alan T Villavicencio
Journal:  J Neurosurg Spine       Date:  2013-12-20

Review 5.  Functional outcome of computer-assisted spinal pedicle screw placement: a systematic review and meta-analysis of 23 studies including 5,992 pedicle screws.

Authors:  Rajeev Verma; Sonal Krishan; Kurt Haendlmayer; A Mohsen
Journal:  Eur Spine J       Date:  2010-01-06       Impact factor: 3.134

6.  Accuracy of minimally invasive percutaneous thoracolumbar pedicle screws using 2D fluoroscopy: a retrospective review through 3D CT analysis.

Authors:  Mark J Winder; Paul M Gilhooly
Journal:  J Spine Surg       Date:  2017-06

7.  Robotic versus fluoroscopy-guided pedicle screw insertion for metastatic spinal disease: a matched-cohort comparison.

Authors:  Volodymyr Solomiichuk; Julius Fleischhammer; Granit Molliqaj; Jwad Warda; Awad Alaid; Kajetan von Eckardstein; Karl Schaller; Enrico Tessitore; Veit Rohde; Bawarjan Schatlo
Journal:  Neurosurg Focus       Date:  2017-05       Impact factor: 4.047

Review 8.  Complications in spine surgery.

Authors:  Rani Nasser; Sanjay Yadla; Mitchell G Maltenfort; James S Harrop; D Greg Anderson; Alexander R Vaccaro; Ashwini D Sharan; John K Ratliff
Journal:  J Neurosurg Spine       Date:  2010-08

9.  Evaluation of robot-guided minimally invasive implantation of 2067 pedicle screws.

Authors:  Naureen Keric; Christian Doenitz; Amer Haj; Izabela Rachwal-Czyzewicz; Mirjam Renovanz; Dominik M A Wesp; Stephan Boor; Jens Conrad; Alexander Brawanski; Alf Giese; Sven R Kantelhardt
Journal:  Neurosurg Focus       Date:  2017-05       Impact factor: 4.047

10.  [Short-term effectiveness comparison between robotic-guided percutaneous minimally invasive pedicle screw internal fixation and traditional open internal fixation in treatment of thoracolumbar fractures].

Authors:  Shu Lin; Jiang Hu; Lun Wan; Liuyi Tang; Yue Wang; Yang Yu; Wei Zhang
Journal:  Zhongguo Xiu Fu Chong Jian Wai Ke Za Zhi       Date:  2020-01-15
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  1 in total

1.  Artificial Intelligence in Public Health: Current Trends and Future Possibilities.

Authors:  Daniele Giansanti
Journal:  Int J Environ Res Public Health       Date:  2022-09-21       Impact factor: 4.614

  1 in total

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