Latest AI and machine learning research in orthopedics for healthcare professionals.
Given the limitations of unimodal pain recognition approaches, this study aimed to develop a multimodal pain recognition system for older patients with hip fractures using multimodal information fusion. The proposed system employs ResNet-50 for facial expression analysis and a VGG-based (VGGish) network for audio-based pain recognition. A channel attention mechanism was incorporated to refine feat...
Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elevate mortality rates. Consequently, early prevention and identification of this condition are crucial in improving patient prognosis. In this study, clinical indicators pertaining to postoperative pneumonia in patients with lower limb fractures at Nan...
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment....
Patients with lumbar degenerative disease typically undergo preoperative MRI combined with CT scans, but this approach introduces additional ionizing ...
In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conv...
Determining mixed mode fracture parameters asphalt concrete mixtures remains an engineering challenge due to non-homogeneity and inelasticity of the m...
In this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parameters to assess the progressive loss of collagen an...
OBJECTIVE: This study aimed to identify the hyoid bone (HB) using the nnU-Net based artificial intelligence (AI) model in cone beam computed tomograph...
OBJECTIVE: This study aimed to develop and validate a predictive model to detect osteoporosis using radiomic features and machine learning (ML) approa...
BACKGROUND: Osteoarthritis (OA) of the hip is a progressive musculoskeletal disorder characterized by stiffness and limited passive range of motion. H...
OBJECTIVE: Based on preoperative clinical text data and lumbar magnetic resonance imaging (MRI), we applied machine learning (ML) algorithms to constr...
A major issue after total knee replacement (TKR) surgery is asymmetric gait kinetics, which increases knee loads on the non-operated knee. This imbala...
Additive manufacturing (AM) is a powerful approach in healthcare to augment the functionalities of patient-specific medical products and surgical tool...
BACKGROUND: The automated segmentation of computed tomography (CT) images has made their opportunistic use more feasible, yet, the association of musc...
BACKGROUND: Treatment of metastatic spinal disease often involves surgical intervention; however, surgical site infections (SSI) pose a great challeng...
PURPOSE: Patients with recurrent complaints after total knee arthroplasty may suffer from aseptic implant loosening. Current imaging modalities do not...
Graphene oxide (GO) materials have complex chemical structures that are linked to their macroscopic properties. Here we show that first-principles sim...
IMPORTANCE: Deep learning predictions of retinal nerve fiber layer (RNFL) thickness derived from optic disc photographs may help to determine risk for...
The study aims to evaluate the global research landscape of facial bone contouring to identify current hotspots and future research directions. Data w...