Orthopedics

Automated segmentation of magnetic resonance bone marrow signal: a feasibility study.

BACKGROUND: Manual assessment of bone marrow signal is time-consuming and requires meticulous standardisation to secure adequate precision of findings.

BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning.

Detection of the presence and absence of bone invasion by the tumor in oral squamous cell carcinoma (OSCC) patients is very significant for their treatment planning and surgical resection. For bone invasion detection, CT scan imaging is the preferred choice of radiologists because of its high sensitivity and specificity. In the present work, deep learning algorithm based model, , has been proposed...

Use of machine learning to model surgical decision-making in lumbar spine surgery.

PURPOSE: The majority of lumbar spine surgery referrals do not proceed to surgery. Early identification of surgical candidates in the referral process...

A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the Res...

Exploring the use of machine learning for the assessment of skeletal fracture morphology and differentiation between impact mechanisms: A pilot study.

Analyzing and interpreting traumatic injuries is a fundamental aspect of routine forensic case work. As the human skeleton can be impacted through a c...

Natural language processing for automated surveillance of intraoperative neuromonitoring in spine surgery.

We sought to develop natural language processing (NLP) methods for automated detection and characterization of neuromonitoring documentation from free...

Motor Ability Evaluation of the Upper Extremity with Point-To-Point Training Movement Based on End-Effector Robot-Assisted Training System.

Assessment is critical during the procedure of stroke rehabilitation. However, traditional assessment methods are time-consuming, laborious, and depen...

Artificial intelligence and spine imaging: limitations, regulatory issues and future direction.

BACKGROUND: As big data and artificial intelligence (AI) in spine care, and medicine as a whole, continue to be at the forefront of research, careful ...

A Deep Learning Approach for MRI in the Diagnosis of Labral Injuries of the Hip Joint.

BACKGROUND: The diagnosis of labral injury on MRI is time-consuming and potential for incorrect diagnoses.

Multiple instance learning detects peripheral arterial disease from high-resolution color fundus photography.

Peripheral arterial disease (PAD) is caused by atherosclerosis and is a common disease of the elderly leading to excess morbidity and mortality. Early...

External validation of deep learning-based bone-age software: a preliminary study with real world data.

Artificial intelligence (AI) is increasingly being used in bone-age (BA) assessment due to its complicated and lengthy nature. We aimed to evaluate th...

Dynamic Invariant-Specific Representation Fusion Network for Multimodal Sentiment Analysis.

Multimodal sentiment analysis (MSA) aims to infer emotions from linguistic, auditory, and visual sequences. Multimodal information representation meth...

An AI-based Prediction Model for Drug-drug Interactions in Osteoporosis and Paget's Diseases from SMILES.

The skeleton is one of the most important organs in the human body in assisting our motion and activities; however, bone density attenuates gradually ...

DeLUCS: Deep learning for unsupervised clustering of DNA sequences.

We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence h...

A CT Image-Based Virtual Sensing Method to Estimate Bone Drilling Force for Surgical Robots.

OBJECTIVE: Current surgical robots face challenges to understand preoperative images like human surgeons, which hindering robots from making full use ...

Efficacy and Applications of Artificial Intelligence and Machine Learning Analyses in Total Joint Arthroplasty: A Call for Improved Reporting.

BACKGROUND: There has been a considerable increase in total joint arthroplasty (TJA) research using machine learning (ML). Therefore, the purposes of ...

Quantification of uptake in pelvis F-18 FLT PET-CT images using a 3D localization and segmentation CNN.

PURPOSE: The purpose of this work was to develop and validate a deep convolutional neural network (CNN) approach for the automated pelvis segmentation...

Forensic bone age estimation of adolescent pelvis X-rays based on two-stage convolutional neural network.

In the forensic estimation of bone age, the pelvis is important for identifying the bone age of teenagers. However, studies on this topic remain insuf...

Machine learning assisted real-time deformability cytometry of CD34+ cells allows to identify patients with myelodysplastic syndromes.

Diagnosis of myelodysplastic syndrome (MDS) mainly relies on a manual assessment of the peripheral blood and bone marrow cell morphology. The WHO guid...

Biohybrid Variable-Stiffness Soft Actuators that Self-Create Bone.

Inspired by the dynamic process of initial bone development, in which a soft tissue turns into a solid load-bearing structure, the fabrication, optimi...