Orthopedics

Deep Learning Preoperatively Predicts Value Metrics for Primary Total Knee Arthroplasty: Development and Validation of an Artificial Neural Network Model.

BACKGROUND: The objective is to develop and validate an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition before primary total knee arthroplasty (TKA). The secondary objective applied the ANN to propose a risk-based, patient-specific payment model (PSPM) commensurate with case complexity.

Letter to the Editor on "Robot-Assisted Total Knee Arthroplasty Does Not Improve Long-Term Clinical and Radiologic Outcomes".

Artificial Intelligence and Arthroplasty at a Single Institution: Real-World Applications of Machine Learning to Big Data, Value-Based Care, Mobile Health, and Remote Patient Monitoring.

BACKGROUND: Driven by the recent ubiquity of big data and computing power, we established the Machine Learning Arthroplasty Laboratory (MLAL) to exami...

Response to Letter to the Editor on "Robot-Assisted Total Knee Arthroplasty Does Not Improve Long-Term Clinical and Radiologic Outcomes".

Intelligent prediction of kinetic parameters during cutting manoeuvres.

Due to its capabilities in analysing injury risk, the ability to analyse an athlete's ground reaction force and joint moments is of high interest in s...

Development of Machine Learning Algorithms for Prediction of Sustained Postoperative Opioid Prescriptions After Total Hip Arthroplasty.

BACKGROUND: Postoperative recovery after total hip arthroplasty (THA) can lead to the development of prolonged opioid use but there are few tools for ...

Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss.

Knee osteoarthritis (OA) is one major cause of activity limitation and physical disability in older adults. Early detection and intervention can help ...

Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review.

BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poise...

Deep Learning for the Radiographic Detection of Periodontal Bone Loss.

We applied deep convolutional neural networks (CNNs) to detect periodontal bone loss (PBL) on panoramic dental radiographs. We synthesized a set of 20...

Transforaminal Posterior Approach Is Effective for Treatment of Lower Thoracic Spine Spondylodiscitis.

BACKGROUND: Patients with lower-thoracic spine pathologies that affect anterior column stability and compress the neural tissues need anterior decompr...

Artificial neural network optimizes self-examination of osteoporosis risk in women.

OBJECTIVE: This study aimed to investigate the application of an artificial neural network (ANN) in optimizing the Osteoporosis Self-Assessment Tool f...

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use c...

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11.

BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostate cancer, it would be of value to use objective to...

Task-Oriented Feature-Fused Network With Multivariate Dataset for Joint Face Analysis.

Deep multitask learning for face analysis has received increasing attentions. From literature, most existing methods focus on optimizing a main task b...

Artificial Intelligence in Musculoskeletal Imaging: Current Status and Future Directions.

The objective of this article is to show how artificial intelligence (AI) has impacted different components of the imaging value chain thus far as we...

Comparison between navigated reported position and postoperative computed tomography to evaluate accuracy in a robotic navigation system in total knee arthroplasty.

BACKGROUND: Computer navigation increases reproducibility compared to non-navigated total knee arthroplasty (TKA). Robotics navigation is a branch of ...

Predicting Inpatient Payments Prior to Lower Extremity Arthroplasty Using Deep Learning: Which Model Architecture Is Best?

BACKGROUND: Recent advances in machine learning have given rise to deep learning, which uses hierarchical layers to build models, offering the ability...

Development of a deep neural network for generating synthetic dual-energy chest x-ray images with single x-ray exposure.

Dual-energy chest radiography (DECR) is a medical imaging technology that can improve diagnostic accuracy. This technique can decompose single-energy ...

In situ tissue classification during laser ablation using acoustic signals.

We suggest a novel method to classify the type of tissue that is being ablated, using the recorded acoustic sound waves during pulsed ultraviolet lase...

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.

BACKGROUND: The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathoge...