Emergency Medicine

Development of Insert Condition Classification System for CNC Lathes Using Power Spectral Density Distribution of Accelerometer Vibration Signals.

Insert conditions significantly influence the product quality and manufacturing efficiency of lathe machining. This study used the power spectral density distribution of the vibration signals of a lathe machining accelerometer to design an insert condition classification system applicable to different machining conditions. For four common lathe machining insert conditions (i.e., built-up edge, fla...

Comparative Analysis of Cutting Forces, Torques, and Vibration in Drilling of Bovine, Porcine, and Artificial Femur Bone with Considerations for Robot Effector Stiffness.

Bone drilling is known as one of the most sensitive milling processes in biomedical engineering field. Fracture behavior of this cortical bone during drilling has attracted the attention of many researchers; however, there are still impending concerns such as necrosis, tool breakage, and microcracks due to high cutting forces, torques, and high vibration while drilling. This paper presents a compa...

Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

BACKGROUND: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. E...

Identification of Patients with Nontraumatic Intracranial Hemorrhage Using Administrative Claims Data.

INTRODUCTION: Nontraumatic intracranial hemorrhage (ICH) is a neurological emergency of research interest; however, unlike ischemic stroke, has not be...

Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach.

Cerebral Microbleeds (CMBs) are small chronic brain hemorrhages, which have been considered as diagnostic indicators for different cerebrovascular dis...

Anaerobic condition induces a viable but nonculturable state of the PCB-degrading Bacteria Rhodococcus biphenylivorans TG9.

Significant microbial removal of highly chlorinated polychlorinated biphenyls (PCBs) requires the cooperation of anaerobic and aerobic bacteria. Durin...

Computer-Aided Fracture Size Measurement in Orbital Fractures-An Alternative to Manual Evaluation.

OBJECTIVE: We aimed to present a novel semiautomated tool for orbital fracture size measurement and to compare the variability of the proposed method ...

Predicting defibrillation success in out-of-hospital cardiac arrested patients: Moving beyond feature design.

OBJECTIVE: Optimizing timing of defibrillation by evaluating the likelihood of a successful outcome could significantly enhance resuscitation. Previou...

Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.

The goals of this study were to develop a risk prediction model in unmet dental care needs and to explore the intersection between social determinants...

Cleaning Up the MESS: Can Machine Learning Be Used to Predict Lower Extremity Amputation after Trauma-Associated Arterial Injury?

BACKGROUND: Thirty years after the Mangled Extremity Severity Score was developed, advances in vascular, trauma, and orthopaedic surgery have rendered...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the development and scale-up of novel AI interventions to aid i...

Lignin-Incorporated Nanogel Serving As an Antioxidant Biomaterial for Wound Healing.

Oxidative phosphorylation is an important biological process in the body to produce energy, during which oxygen free radicals are generated as byprodu...

Accurate and Efficient Intracranial Hemorrhage Detection and Subtype Classification in 3D CT Scans with Convolutional and Long Short-Term Memory Neural Networks.

In this paper, we present our system for the RSNA Intracranial Hemorrhage Detection challenge, which is based on the RSNA 2019 Brain CT Hemorrhage dat...

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.

IMPORTANCE: Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with a...

Deep-learning-based enhanced optic-disc photography.

Optic-disc photography (ODP) has proven to be very useful for optic nerve evaluation in glaucoma. In real clinical practice, however, limited patient ...

Machine learning prediction of the adverse outcome for nontraumatic subarachnoid hemorrhage patients.

OBJECTIVE: Subarachnoid hemorrhage (SAH) is often devastating with increased early mortality, particularly in those with presumed delayed cerebral isc...

3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials.

Intracranial hemorrhage (ICH) occurs when a blood vessel ruptures in the brain. This leads to significant morbidity and mortality, the likelihood of w...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopat...

Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.

Multi-site training methods for artificial neural networks are of particular interest to the medical machine learning community primarily due to the d...

Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock.

BACKGROUND: Access to quantitative information is crucial to obtain a deeper understanding of biological systems. In addition to being low-throughput,...