Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review

CLA Navarro, JAA Damen, T Takada, SWJ Nijman… - bmj, 2021 - bmj.com
Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Artificial intelligence-driven prediction modeling and decision making in spine surgery using hybrid machine learning models

B Saravi, F Hassel, S Ülkümen, A Zink… - Journal of Personalized …, 2022 - mdpi.com
Healthcare systems worldwide generate vast amounts of data from many different sources.
Although of high complexity for a human being, it is essential to determine the patterns and …

[HTML][HTML] Machine learning in infection management using routine electronic health records: tools, techniques, and reporting of future technologies

CF Luz, M Vollmer, J Decruyenaere, MW Nijsten… - Clinical Microbiology …, 2020 - Elsevier
Background Machine learning (ML) is increasingly being used in many areas of health care.
Its use in infection management is catching up as identified in a recent review in this journal …

Spinal epidural abscess: diagnosis, management, and outcomes

JH Schwab, AA Shah - JAAOS-Journal of the American Academy …, 2020 - journals.lww.com
An infection of the spinal epidural space, spinal epidural abscess (SEA) is a potentially
devastating entity that is rising in incidence. Its insidious presentation, variable progression …

Development of machine learning algorithms to predict patient dissatisfaction after primary total knee arthroplasty

KN Kunze, EM Polce, AJ Sadauskas… - The Journal of arthroplasty, 2020 - Elsevier
Background Postoperative dissatisfaction after primary total knee arthroplasty (TKA) that
requires additional care or readmission may impose a significant financial burden to …

[HTML][HTML] A review on the use of artificial intelligence in spinal diseases

P Azimi, T Yazdanian, EC Benzel, HN Aghaei… - Asian Spine …, 2020 - ncbi.nlm.nih.gov
Artificial neural networks (ANNs) have been used in a wide variety of real-world applications
and it emerges as a promising field across various branches of medicine. This review aims …

Potential benefits, unintended consequences, and future roles of artificial intelligence in orthopaedic surgery research: a call to emphasize data quality and indications

KN Kunze, M Orr, V Krebs, M Bhandari… - Bone & joint …, 2022 - boneandjoint.org.uk
Artificial intelligence and machine-learning analytics have gained extensive popularity in
recent years due to their clinically relevant applications. A wide range of proof-of-concept …

Machine learning algorithms predict clinically significant improvements in satisfaction after hip arthroscopy

KN Kunze, EM Polce, J Rasio, SJ Nho - Arthroscopy: The Journal of …, 2021 - Elsevier
Purpose To develop machine learning algorithms to predict failure to achieve clinically
significant satisfaction after hip arthroscopy. Methods We queried a clinical repository for …

Fostering reproducibility and generalizability in machine learning for clinical prediction modeling in spine surgery

TD Azad, J Ehresman, AK Ahmed, VE Staartjes… - The Spine Journal, 2021 - Elsevier
As the use of machine learning algorithms in the development of clinical prediction models
has increased, researchers are becoming more aware of the deleterious effects that stem …

Diagnostic performance of artificial intelligence for detection of anterior cruciate ligament and meniscus tears: A systematic review

KN Kunze, DM Rossi, GM White, AV Karhade… - … : The Journal of …, 2021 - Elsevier
Purpose To (1) determine the diagnostic efficacy of artificial intelligence (AI) methods for
detecting anterior cruciate ligament (ACL) and meniscus tears and to (2) compare the …