Orthopedics

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 language models (LLMs) have demonstrated success in extracting information from free-text data across various domains. This study evaluates the performance of multiple small LLMs as information extractors on Polish medical notes. MATERIALS AND METHODS:...

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 study analyzed data from five NHANES cycles (2005-2010, 2013-2014, 2017-2018). Multivariate logistic regression and subgroup analyses were conducted to evaluate the relationship between DI-GM and osteoporosis at specific skeletal sites. Restricted cubi...

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...

Changes in computed tomography derived muscle and pulmonary tissue in patients hospitalized for COVID-19: a 12-month follow-up study.

BACKGROUND: Prolonged muscle loss and persistent pulmonary radiological manifestations have been observed among previously hospitalized COVID-19 patie...

SaintGSE: Transformer-based efficient and explainable gene set enrichment analysis.

OBJECTIVE: Gene set enrichment analysis (GSEA) is widely used to interpret genome-wide expression data, but pathway inference from differentially expr...

Imaging without biology: limitations of CT-derived psoas muscle volume as a standalone diagnostic criterion for sarcopenia.

We comment on the study by Choi et al., which proposes CT-derived psoas muscle volume (PV) as a diagnostic indicator for sarcopenia. The study is well...

Comparative performance analysis of AI-based large language models in assessing cervical vertebral maturation stages on lateral cephalometric radiographs.

Time-to-event risk prediction of dual sensory loss in middle-aged patients with symptomatic knee osteoarthritis: model development, preliminary external validation, and explainability analysis.

BACKGROUND: Knee osteoarthritis (KOA) is a highly prevalent chronic condition that substantially impairs functional capacity and quality of life among...

LMO7-mediated ubiquitination of SIRT3 promotes osteoarthritis progression: an investigation using machine learning and molecular dynamics simulations.

BACKGROUND: This study aims to inform clinical decision-making by identifying metabolism-related biomarkers involved in the progression of osteoarthri...

The application of large language models in orthopedic postgraduate education: potentials, challenges, and future prospects.

With the widespread integration of artificial intelligence (AI), orthopedics postgraduate education is transitioning into the intelligent era. Large l...

Mechanobiological design strategy for additively manufacturable tibial ankle implant for enhanced biomechanical and osseointegration performance: A finite element and machine learning approach.

The leading cause of revision surgeries in ankle arthroplasty is aseptic loosening of the tibial implant, resulting from adverse bone remodelling and ...

Noninvasive Prediction of Bone Metastasis-Free Survival in Lung Adenocarcinoma Using Interpretable CT-based Deep Learning Model.

RATIONALE AND OBJECTIVES: Preoperatively identifying patients at high risk of bone metastasis (BM) remains challenging in resectable lung adenocarcino...