AIMC Topic: Arthroplasty, Replacement, Hip

Clear Filters Showing 141 to 150 of 151 articles

Letter to the Editor on "Artificial Intelligence to Identify Arthroplasty Implants From Radiographs of the Hip".

The Journal of arthroplasty Apr 1, 2021
Artificial Intelligence Radiography Prostheses and Implants Humans Arthroplasty, Replacement, Hip
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Does robotic assisted technology improve the accuracy of acetabular component positioning in patients with DDH?

Journal of orthopaedic surgery (Hong Kong) Jan 1, 2021
BACKGROUND: Accurate positioning of the acetabular component is key in performing total hip arthroplasty (THA). However, reconstruction of the acetabulum in the setting of developmental dysplasia of the hip (DDH) is a challenge. Robotic assisted THA ...
Robotics Robotic Surgical Procedures Arthroplasty, Replacement, Hip Hip Prosthesis Humans Acetabulum
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[Intraoperative assessment of pelvic tilt and cup position in total hip arthroplasty: the relevance of navigation and robotics].

Der Orthopade Oct 1, 2020
The optimal 3D positioning of the prosthesis components is of great importance for the stability and function of a total hip endoprosthesis. Pelvic tilt has a particular influence on the position of the implant. In order to use intraoperatively the k...
Arthroplasty, Replacement, Hip Hip Prosthesis Humans Acetabulum Tomography, X-Ray Computed Robotics Surgery, Computer-Assisted
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Data for registry and quality review can be retrospectively collected using natural language processing from unstructured charts of arthroplasty patients.

The bone & joint journal Jul 1, 2020
AIMS: Natural Language Processing (NLP) offers an automated method to extract data from unstructured free text fields for arthroplasty registry participation. Our objective was to investigate how accurately NLP can be used to extract structured clini...
Humans Algorithms Retrospective Studies Arthroplasty, Replacement, Hip Arthroplasty, Replacement, Knee Quality of Health Care Information Storage and Retrieval Natural Language Processing Registries Data Accuracy
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Use of Natural Language Processing Algorithms to Identify Common Data Elements in Operative Notes for Total Hip Arthroplasty.

The Journal of bone and joint surgery. American volume Nov 6, 2019
BACKGROUND: Manual chart review is labor-intensive and requires specialized knowledge possessed by highly trained medical professionals. Natural language processing (NLP) tools are distinctive in their ability to extract critical information from raw...
Humans Algorithms Common Data Elements Electronic Health Records Natural Language Processing Arthroplasty, Replacement, Hip
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Bundled Care for Hip Fractures: A Machine-Learning Approach to an Untenable Patient-Specific Payment Model.

Journal of orthopaedic trauma Jul 1, 2019
OBJECTIVES: With the transition to a value-based model of care delivery, bundled payment models have been implemented with demonstrated success in elective lower extremity joint arthroplasty. Yet, hip fracture outcomes are dependent on patient-level ...
Humans Machine Learning Bayes Theorem Medicare Patient Care Bundles Arthroplasty, Replacement, Hip Health Care Costs Middle Aged Female Health Expenditures Length of Stay Aged Hip Fractures United States Male
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A Predictive Model for Determining Patients Not Requiring Prolonged Hospital Length of Stay After Elective Primary Total Hip Arthroplasty.

Anesthesia and analgesia Jul 1, 2019
BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty. Accurately predicting LOS is important to expectantly manage bed utilization and other hospital resources. We aimed to develop a predictive model for...
Arthroplasty, Replacement, Hip Treatment Outcome Predictive Value of Tests Elective Surgical Procedures Aged Male Middle Aged Risk Assessment Length of Stay Time Factors Retrospective Studies Female Risk Factors Humans Machine Learning Decision Support Techniques
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Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Clinical orthopaedics and related research Jun 1, 2019
BACKGROUND: Identifying patients at risk of not achieving meaningful gains in long-term postsurgical patient-reported outcome measures (PROMs) is important for improving patient monitoring and facilitating presurgical decision support. Machine learni...
Disability Evaluation Humans Registries Retrospective Studies Male Machine Learning Patient Reported Outcome Measures Arthroplasty, Replacement, Knee Female Arthroplasty, Replacement, Hip Middle Aged Aged Minimal Clinically Important Difference Predictive Value of Tests
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Editor's Spotlight/Take 5: Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?

Clinical orthopaedics and related research Jun 1, 2019
Arthroplasty, Replacement, Knee Patient Reported Outcome Measures Arthroplasty, Replacement, Hip Minimal Clinically Important Difference Predictive Value of Tests Humans Disability Evaluation Aged Machine Learning Registries Male Retrospective Studies Middle Aged Female
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[Clinical research on perioperative restrictive fluid therapy combined with preoperative urination training in total hip arthroplasty].

Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery Nov 15, 2017
OBJECTIVE: To evaluate the effectiveness and safety of restrictive fluid therapy combined with preoperative urination training during perioperative period in an enhanced recovery after surgery (ERAS) program for primary total hip arthroplasty (THA).
Urination Fluid Therapy Humans Urination Disorders Prospective Studies Arthroplasty, Replacement, Hip Retrospective Studies
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