Orthopedics

Towards automated joint detection in sleep studies: bridging clinical insight and artificial intelligence.

STUDY OBJECTIVES: To develop and evaluate artificial intelligence methods for detecting upper-body joint positions from video recordings of individuals during sleep, providing a foundation for future automated, video-based analysis of sleep movements that extends beyond conventional sensor-based methods. METHODS: We developed HypnoPose and tested five different model configurations. We pretrained ...

Accuracy assessment of an artificial intelligence model in predicting intraoperative bone resection parameters for robotic-assisted total knee arthroplasty.

Advances in Oral Cavity Stem Cell Research Revealed through Multi-omics Analysis.

Oral stem cell research encompasses the study of dental pulp stem cells, periodontal ligament stem cells, regeneration of dental pulp and periodontal ...

Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images.

OBJECTIVES: To develop a deep learning-based multi-class segmentation model for the simultaneous segmentation of key periodontal structures, including...

Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity.

The AIXA Osteo model architecture (X1AI-Osteo) has undergone internal validation in Taiwan, demonstrating its capability to evaluate osteoporosis and ...

Single-cell sequencing and machine learning-based prediction of spliceosome-associated factor 2 may represent potential targets for osteoarthritis.

BACKGROUND: Osteoarthritis has become a global health challenge due to its complex pathologic mechanisms. Spliceosome-associated factor 2 (SYF2) has b...

Development of machine learning models for preoperative prediction of insufficient clinical improvement after anterior cruciate ligament reconstruction.

[Advances in oral and craniofacial bone regeneration modulated by stem cells and biomaterials].

Cranio-maxillofacial bone defects resulting from trauma, tumors, infection, or congenital malformations not only severely impair patients' physiologic...

Automated vertebral heart size estimation from thoracic radiographs in dogs with AI-assisted clinical decision support.

Cardiomegaly is a clinically significant indicator of cardiac disease in canine companion animals, where early and accurate detection is essential for...

Accelerating real-world data collection using large language models in rare neoplasms: a bone sarcoma example.

BACKGROUND: Real-world data collection in oncology remains a challenge due to the complex and unstructured format of medical notes. Recently, large la...

Association of the Dietary Index for Gut Microbiota with site-specific Osteoporosis: Insights from machine learning applied to a national population.

BACKGROUND: The association between the Dietary Index for Gut Microbiota (DI-GM) and site-specific osteoporosis risk remains unclear. METHODS: This st...

Incorporating artificial intelligence into morphological diagnosis of acute leukemias: Current landscape, challenges and prospects (Review).

Acute leukemias (ALs) are a diverse group of hematological malignancies characterized by the abnormal proliferation of immature cells. Microscopic obs...

Independent bone-level diagnostic accuracy study of an AI tool for detecting appendicular skeletal fractures on radiographs.

OBJECTIVES: To perform an in-depth evaluation of the diagnostic test accuracy of a commercially available AI tool for assistance in fracture detection...

Automated Classification of Alveolar Bone Defects for Preoperative Augmentation Planning Using Deep Learning.

OBJECTIVES: Determining alveolar bone deficiencies prior to dental implant surgeries is critical for surgical planning. This study aimed to develop a ...

Elucidating formability limits in warm incremental sheet forming of AZ61 magnesium alloy using integrated grey relational and data-driven analysis.

The growing demand for lightweight structural components in the automotive and aerospace sectors has intensified interest in magnesium alloys; however...

The SPECT/CT radiomics-based classification of skeletal metastases and benign bone lesions.

Hybrid Single Photon Emission Computed Tomography/Computed Tomography (SPECT/CT) improves lesion localization and diagnostic accuracy in detecting ske...

Fractional-order differential model for knee implant recovery in smart health infrastructures.

Recovery from knee replacement surgery in conventional orthopaedic healthcare systems can be delayed due to high costs, pain, limited monitoring, and ...

Leveraging deep learning to infer continuous predictions from ordinal labels in medical imaging.

In clinical medicine, variables like disease severity are often categorized into discrete ordinal labels such as normal/mild/moderate/severe. However,...

Machine Learning Using Preoperative Patient Factors Can Predict the Severity of Pain Following Primary Total Hip Arthroplasty.

BACKGROUND: Persistent postoperative pain is a challenge in total hip arthroplasty (THA), yet a lack of accurate predictive tools exists for this outc...

The Assessment of Coronal Plane Lower-Limb Alignment on Pre- and Postoperative Long-Leg Radiographs Using Deep Learning.

INTRODUCTION: Coronal plane lower-limb alignment, defined by metrics including the hip-knee-ankle angle (HKAA), lateral distal femoral angle (LDFA), a...