Orthopedics

Improving acute lymphoblastic leukemia diagnosis through CBAM-enhanced VGG19 deep learning.

Acute Lymphoblastic Leukemia (ALL) is an aggressive blood cancer that requires rapid and accurate diagnosis. Manual review of blood and bone marrow smears is time-consuming and observer-dependent, underscoring the need for automated methods. This study presents a deep learning framework with attention mechanisms for automated detection and subtyping of ALL from microscopic bone marrow images, incl...

A physics-informed hybrid ML framework for pore pressure and fracture gradient prediction in carbonate reservoirs.

Accurate prediction of formation pore pressure and fracture gradient is essential for safe mud-weight selection and wellbore stability, especially in heterogeneous offshore carbonate reservoirs. Classical empirical methods (Eaton, Miller, and Zhang) often degrade in such settings, while purely data-driven models can be hard to justify when calibration data are sparse. This study presents a physics...

Topological control of spontaneous failure in active nematic solids.

Active solids using energy influx to generate non-equilibrium forces undergo spontaneous mechanical failure, but how topological defects concentrate i...

De-identification Strategy and Re-identification Risks for Facial Computed Tomography Images via Deep Learning.

The aim is to develop and evaluate a deep learning-based selective de-identification method for head computed tomography (CT) images that removes faci...

Automated classification of shoulder radiology focusing on cuff tear arthropathy and glenoid erosion using AI.

BACKGROUND: Recent advancements in the field artificial intelligence (AI), particularly in the architecture of convolutional neural network (CNN) arch...

Self-Supervised joint flow and depth estimation via Multi-Cue uncertainty modeling.

Understanding motion and 3D structure from dynamic scenes is a fundamental computer vision challenge. Unsupervised learning addresses the high cost of...

Large-scale analysis of DNA quantification metrics and SNP sequencing performance in unidentified human remains.

Massively parallel sequencing (MPS)-based single nucleotide polymorphism (SNP) profiling is being increasingly used in forensic DNA testing, yet the i...

Diagnostic accuracy of deep learning vs. human raters for detecting osteoporotic vertebral compression fractures in routine CT scans.

OBJECTIVES: Vertebral fractures are severe complications of osteoporosis but are frequently missed on computed tomography (CT). Differentiating true f...

Machine learning guided resolution of mechanical trade-off in polymer composites via stress adaptive interface.

Developing polymer composites that simultaneously achieve high strength, toughness, and impact resistance remains a fundamental challenge due to inher...

Contextual anatomy-guided deep learning for accurate fovea segmentation in diabetic retinopathy fundus images.

Accurate fovea segmentation in fundus images is a critical step in diabetic retinopathy screening; however, it remains a challenging task due to the i...

The SEWAbility system: a video-based job analysis framework for understanding task-specific job demands.

This study introduces the Smart Evaluation of Work Ability (SEWAbility), an AI-powered video analysis system designed to support objective job analysi...

Comment on "Automatic rib fracture detection on postmortem CT data using deep learning".

Two -stage contrastive learning framework for vertebral compression fracture screening in frontal chest X-ray.

Vertebral Compression Fractures (VCFs) are early signs of osteoporosis and the most common type of osteoporotic fracture. In clinical practice, the pi...

Can AI write reports like a radiologist? A blinded evaluation of large language model-generated lumbar spine MRI reports.

BACKGROUND: To compare the quality and clinical usefulness of large language model (LLM)-generated lumbar spine magnetic resonance imaging (MRI) repor...

Deep learning pipeline for trapezium segmentation in thumb radiographs.

OBJECTIVE: Accurate identification of the trapezium is crucial for trapeziometacarpal (TMC) arthroplasty but remains challenging on standard radiograp...

Bibliometric analysis of bone metastasis from prostate cancer research from 2007 to 2024.

BACKGROUND: Prostate cancer (PCa) is one of the most common cancer in men worldwide, while numerous scientific achievements have been made in research...

Predicting Geriatric Rehabilitation Stays of ≤4 Weeks After Hip Fracture Surgery: Machine Learning Approach Using Physical Activity and Patient Data.

BACKGROUND: In 2022, over 18,000 patients aged ≥70 years were hospitalized in the Netherlands for a hip fracture, with 50% requiring geriatric rehabil...

Graph clustering and prediction models for DISC-based personality and competency analysis.

Machine learning-based prediction and quantification of OCD surgery and pedigree effects on racehorse performance.

Osteochondritis dissecans (OCD) is a common developmental orthopedic condition in Thoroughbred racehorses and although arthroscopic surgery is widely ...

Validity of a novel web application for measuring active range of motion and its reliability as a self-measurement method in telerehabilitation.

PURPOSE: As a result of the emergence of Artificial Intelligence (AI), new applications for measuring active range of motion (AROM) in telerehabilitat...