ReviewKnee surgery, sports traumatology, arthroscopy : official journal of the ESSKA2023
Supervised machine learning and associated algorithms: applications in orthopedic surgery.
Review in Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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.
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.
Who cites it
30 citing papers in PubMed.
- Integrating Artificial Intelligence into Orthopedic Practice: Modeling Attitudes and Intentions to Use AI.Healthcare (Basel, Switzerland) · 2026Article
- Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Review
- Prevalence and Associated Factors of Frailty in Middle-Aged and Elderly Patients with Atrial Fibrillation: An Exploratory Machine Learning Analysis.Clinical interventions in aging · 2026Article
- From de-skilling to up-skilling: How artificial intelligence will augment the modern physician.Journal of experimental orthopaedics · 2026Review
- Personalizing fall fear prevention in knee osteoarthritis: an interpretable prediction framework via IGKSO synchronous optimization and SHAP-based risk stratification.Frontiers in public health · 2026Article
- Artificial intelligence and robotic technologies redefining precision and personalization in orthopedic surgery: a narrative review.Frontiers in bioengineering and biotechnology · 2026Review
- Artificial intelligence agents in orthopaedics: Concepts, capabilities and the road ahead.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Review
- Using multiple machine learning algorithms to predict spinal cord injury in patients with cervical spondylosis: a multicenter study.Scientific reports · 2025Article
- A practical guide to the implementation of artificial intelligence in orthopaedic research-Part 3: How orthopaedic research benefits from the implementation of artificial intelligence.Journal of experimental orthopaedics · 2025Review
- Machine learning algorithms for prediction of cerebrospinal fluid leakage after posterior surgery for thoracic ossification of the ligamentum flavum.Scientific reports · 2025Article
- Artificial Intelligence in Orthopedic Surgery: Current Applications, Challenges, and Future Directions.MedComm · 2025Review
- Using deep learning to predict postoperative pain in reverse shoulder arthroplasty patients.JSES international · 2025Article
- Exploring the Role of microRNAs as Blood Biomarkers in Alzheimer's Disease and Frontotemporal Dementia.International journal of molecular sciences · 2025Review
- Machine-learning models for shoulder rehabilitation exercises classification using a wearable system.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2025Article
- A systematic review of machine learning applications in predicting opioid associated adverse events.NPJ digital medicine · 2025Article
- Develop and validate a machine learning model to predict the risk of persistent pain after percutaneous transforaminal endoscopic discectomy.Frontiers in surgery · 2025Article
- Establishment and comparison of three fear of progression risk prediction models for gynecological malignancies patients based on machine learning.Frontiers in oncology · 2025Article
- Artificial intelligence in medical and biological research: promise and perils of ChatGPT and DeepSeek in advancing healthcare.Turkish journal of biology = Turk biyoloji dergisi · 2025Review
- The role of artificial intelligence in the management of liver diseases.The Kaohsiung journal of medical sciences · 2024Review
- Simulation of osteotomy in total knee arthroplasty with femoral extra-articular deformity assisted by artificial intelligence: a study based on three-dimensional models.Journal of orthopaedic surgery and research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Supervised learning is the most common form of machine learning utilized in medical research. It is used to predict outcomes of interest or classify positive and/or negative cases with a known ground truth. Supervised learning describes a spectrum of techniques, ranging from traditional regression modeling to more complex tree boosting, which are becoming increasingly prevalent as the focus on "big data" develops. While these tools are becoming increasingly popular and powerful, there is a paucity of literature available that describe the strengths and limitations of these different modeling techniques. Typically, there is no formal training for health care professionals in the use of machine learning models. As machine learning applications throughout medicine increase, it is important that physicians and other health care professionals better understand the processes underlying application of these techniques. The purpose of this study is to provide an overview of commonly used supervised learning techniques with recent case examples within the orthopedic literature. An additional goal is to address disparities in the understanding of these methods to improve communication within and between research teams.
Indexed as
Identifiers
36222893What OpenQuestion holds
Registered trials
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.