Orthopedics

AI classification of knee prostheses from plain radiographs and real-world applications.

PURPOSE: Total knee arthroplasty (TKA) is considered the gold standard treatment for end-stage knee osteoarthritis. Common complications associated with TKA include implant loosening and periprosthetic fractures, which often require revision surgery or fixation. Challenges arise when medical records related to the knee prosthesis are lost, making it difficult to plan for revision surgery effective...

Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors.

BACKGROUND: Periprosthetic joint infection leads to significant morbidity and mortality after total knee arthroplasty. Preoperative and perioperative risk prediction and assessment tools are lacking in Asia. This study developed the first machine learning model for individualized prediction of periprosthetic joint infection following primary total knee arthroplasty in this demographic.

Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?

OBJECTIVE: This study was designed to establish a diagnostic model for osteoporosis by collecting clinical information from patients with and without ...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitat...

Using statistical modelling and machine learning in detecting bone properties: A systematic review protocol.

INTRODUCTION: Osteoporosis, a common condition characterised by decreased bone mass and microarchitectural deterioration, leading to increased fractur...

Optimization of primary screw stability in Trabecular bone using neural network-based models.

BACKGROUND AND OBJECTIVE: Screw implant stability in bone is crucial to the success of many orthopaedic procedures, yet the relationship between screw...

Direct-to-Treatment Adaptive Radiation Therapy: Live Planning of Spine Metastases Using Novel Cone Beam Computed Tomography.

PURPOSE: Cone beam computed tomography (CBCT)-based online adaptive radiation therapy is carried out using a synthetic CT (sCT) created through deform...

Validity of recurrent neural networks to predict pedal forces and lower limb kinetics in cycling.

Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury prevention. Measuring pedal forces and joint moments ...

Ensemble-learning approach improves fracture prediction using genomic and phenotypic data.

UNLABELLED: This study presents an innovative ensemble machine learning model integrating genomic and clinical data to enhance the prediction of major...

Advance signal processing and machine learning approach for analysis and classification of knee osteoarthritis vibroarthrographic signals.

Osteoarthritis is a common cause of disability among elderly significantly affecting their quality of life due to pain and functional limitations. Thi...

Machine Learning Predicts Non-Preferred and Preferred Vertebrate Hosts of Tsetse Flies (Glossina spp.) Based on Skin Volatile Emission Profiles.

Tsetse fly vectors of African trypanosomosis preferentially feed on certain vertebrates largely determined by olfactory cues they emit. Previously, we...

An explainable machine learning-based prediction model for sarcopenia in elderly Chinese people with knee osteoarthritis.

BACKGROUND: Sarcopenia is an age-related progressive skeletal muscle disease that leads to loss of muscle mass and function, resulting in adverse heal...

Machine learning models accurately predict clades of proteocephalidean tapeworms (Onchoproteocephalidea) based on host and biogeographical data.

Proteocephalids are a cosmopolitan and diverse group of tapeworms (Cestoda) that have colonized vertebrate hosts in freshwater and terrestrial environ...

Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images.

Whole-body bone scan (WBS) is usually used as the effective diagnostic method for early-stage and comprehensive bone metastases of breast cancer. WBS ...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone mass andsevere resorption in dental implant therapy....

A Joint LLM-KG System for Disease Q&A.

Medical question answer (QA) assistants respond to lay users' health-related queries by synthesizing information from multiple sources using natural l...

Measuring the severity of knee osteoarthritis with an aberration-free fast line scanning Raman imaging system.

Osteoarthritis (OA) is a major cause of disability worldwide, with symptoms like joint pain, limited functionality, and decreased quality of life, pot...

Joint fusion of EHR and ECG data using attention-based CNN and ViT for predicting adverse clinical endpoints in percutaneous coronary intervention patients.

Predicting post-Percutaneous Coronary Intervention (PCI) outcomes is crucial for effective patient management and quality improvement in healthcare. H...

Using deep reinforcement learning to investigate stretch feedback during swimming of the lamprey.

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved...

AI-Generated Synthetic STIR of the Lumbar Spine from T1 and T2 MRI Sequences Trained with Open-Source Algorithms.

BACKGROUND AND PURPOSE: Lumbar spine MRIs can be time consuming, stressful for patients, and costly to acquire. In this work, we train and evaluate op...