Emergency Medicine

Use of pressure-regulated volume control in the first 48 hours of hospitalization of mechanically ventilated patients with sepsis or septic shock, with or without ARDS.

PURPOSE: To evaluate the impact of pressure-regulated volume control (PRVC/VC+) use on delivered tidal volumes in patients with acute respiratory distress syndrome (ARDS) or at risk for ARDS.

Expert-level detection of acute intracranial hemorrhage on head computed tomography using deep learning.

Computed tomography (CT) of the head is used worldwide to diagnose neurologic emergencies. However, expertise is required to interpret these scans, and even highly trained experts may miss subtle life-threatening findings. For head CT, a unique challenge is to identify, with perfect or near-perfect sensitivity and very high specificity, often small subtle abnormalities on a multislice cross-sectio...

Physicochemical stability of an admixture of lidocaine and ketamine in polypropylene syringe used in opioid-free anaesthesia.

OBJECTIVES: Opioid-free anaesthesia is a treatment strategy of pain management based on the use of drugs such as lidocaine, ketamine and dexmedetomidi...

Promoting head CT exams in the emergency department triage using a machine learning model.

PURPOSE: In this study, we aimed to develop a novel prediction model to identify patients in need of a non-contrast head CT exam during emergency depa...

De novo Gastrinoma: A Case Report.

Gastrinomas are neuroendocrine tumors characterized by gastrin overexpression - 80% are sporadic and 20% are associated with multiple endocrine neopla...

Ovarian Toxicity Assessment in Histopathological Images Using Deep Learning.

As ovarian toxicity is often a safety concern for cancer therapeutics, identification of ovarian pathology is important in early stages of preclinical...

Clinical Study on Minimally Invasive Liquefaction and Drainage of Hypertensive Putaminal Hemorrhage through Frontal Approach.

 Hypertensive intracerebral hemorrhage is one of the most common cerebrovascular diseases with high mortality and high disability rate. The aim of th...

Evaluating genotoxicity of metal oxide nanoparticles: Application of advanced supervised and unsupervised machine learning techniques.

Presence of missing data points in datasets is among main challenges in handling the toxicological data for nanomaterials. As the processing of missin...

Prediction Model with High-Performance Constitutive Androstane Receptor (CAR) Using DeepSnap-Deep Learning Approach from the Tox21 10K Compound Library.

The constitutive androstane receptor (CAR) plays pivotal roles in drug-induced liver injury through the transcriptional regulation of drug-metabolizin...

Validation of an alcohol misuse classifier in hospitalized patients.

BACKGROUND: Current modes of identifying alcohol misuse in hospitalized patients rely on self-report questionnaires and diagnostic codes that have lim...

Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces.

OBJECTIVES: To determine the effect of a domain-specific ontology and machine learning-driven user interfaces on the efficiency and quality of documen...

Transplant nephrectomy with peritoneal window: Georgetown University experience.

OBJECTIVES: Transplant nephrectomy is a technically challenging procedure with high complication rates. Morbidity and mortality are mostly due to hemo...

Otoscopic diagnosis using computer vision: An automated machine learning approach.

OBJECTIVE: Access to otolaryngology is limited by lengthy wait lists and lack of specialists, especially in rural and remote areas. The objective of t...

Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry.

Background Detection of vertebral fractures (VFs) aids in management of osteoporosis and targeting of fracture prevention therapies. Purpose To determ...

Could deep learning in neural networks improve the QSAR models?

Assessing chemical toxicity is a multidisciplinary process, traditionally involving in vivo, in vitro and in silico tests. Currently, toxicological go...

Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.

Hunting for chemicals with favorable pharmacological, toxicological, and pharmacokinetic properties remains a formidable challenge for drug discovery....

Machine learning for mixture toxicity analysis based on high-throughput printing technology.

Analysis on mixture toxicity (Mix-tox) of the multi-chemical space is constantly followed with interest for many researchers. Conventional toxicity te...

Sex estimation: a comparison of techniques based on binary logistic, probit and cumulative probit regression, linear and quadratic discriminant analysis, neural networks, and naïve Bayes classification using ordinal variables.

The performance of seven classification methods, binary logistic (BLR), probit (PR) and cumulative probit (CPR) regression, linear (LDA) and quadratic...

Automated detection of altered mental status in emergency department clinical notes: a deep learning approach.

BACKGROUND: Machine learning has been used extensively in clinical text classification tasks. Deep learning approaches using word embeddings have been...

Medical Robotics in Bone Fracture Reduction Surgery: A Review.

Since the advantages of precise operation and effective reduction of radiation, robots have become one of the best choices for solving the defects of ...