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Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.

To improve image quality and CT number accuracy of fast-scan low-dose cone-beam computed tomography ...

Artificial intelligence in pharmacovigilance: Practical utility.

Endocannabinoid degradation inhibitors ameliorate neuronal and synaptic alterations following traumatic brain injury.

Our previous work showed that lateral fluid percussion injury to the sensorimotor cortex (SMC) of an...

Training and Validation of Deep Neural Networks for the Prediction of 90-Day Post-Liver Transplant Mortality Using UNOS Registry Data.

Prediction models of post-liver transplant mortality are crucial so that donor organs are not alloca...

A lesson in implementation: A pre-post study of providers' experience with artificial intelligence-based clinical decision support.

BACKGROUND: To explore attitudes about artificial intelligence (AI) among staff who utilized AI-base...

Utilizing Advanced Technologies to Augment Pharmacovigilance Systems: Challenges and Opportunities.

There are significant challenges and opportunities in deploying and utilizing advanced information t...

Effects of post-weaning supplementation of immunomodulatory feed ingredient on body weight and cortisol concentrations in program-fed beef heifers.

The objective of this study was to determine the effects of an immunomodulatory feed ingredient duri...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and ...

Predicting the occurrence of surgical site infections using text mining and machine learning.

In this study we propose the use of text mining and machine learning methods to predict and detect S...

Radiomics allows for detection of benign and malignant histopathology in patients with metastatic testicular germ cell tumors prior to post-chemotherapy retroperitoneal lymph node dissection.

OBJECTIVES: To evaluate whether a computed tomography (CT) radiomics-based machine learning classifi...

Inactivation of on post-harvest cantaloupe and lettuce by a lytic bacteriophage cocktail.

() is a causative agent of multiple outbreaks of foodborne illness associated with fresh produce, i...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since i...

The neural and neurocomputational bases of recovery from post-stroke aphasia.

Language impairment, or aphasia, is a disabling symptom that affects at least one third of individua...

Fuzzy logic-based clinical decision support system for the evaluation of renal function in post-Transplant Patients.

OBJECTIVES: In the context of the gradual development of artificial intelligence in health care, the...

Development of artificial neural network model for prediction of post-streptococcus mutans in dental caries.

BACKGROUND AND OBJECTIVE: Streptococcus mutans is the primary initiator and most common organism ass...

Comparative analysis on Facebook post interaction using DNN, ELM and LSTM.

This study presents a novel research approach to predict user interaction for social media post usin...

An optimal interval type-2 fuzzy logic control based closed-loop drug administration to regulate the mean arterial blood pressure.

BACKGROUND AND OBJECTIVE: The main aim of this work is to present an optimal and robust controller d...

Association of polymorphisms in , , and with post-induction infliximab trough level in Crohn's disease patients.

BACKGROUND: Trough levels of the post-induction serum infliximab (IFX) are associated with short-ter...

A Multi-Organ Nucleus Segmentation Challenge.

Generalized nucleus segmentation techniques can contribute greatly to reducing the time to develop a...

RedMed: Extending drug lexicons for social media applications.

Social media has been identified as a promising potential source of information for pharmacovigilanc...

Choosing Clinical Variables for Risk Stratification Post-Acute Coronary Syndrome.

Most risk stratification methods use expert opinion to identify a fixed number of clinical variables...