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Robot-Assisted Simple Prostatectomy: A Comparison of Primary Simple Prostatectomy Salvage Simple Prostatectomy in Treatment of Lower Urinary Tract Symptoms.

Simple prostatectomy is indicated in patients with enlarged glands (>80 ) who present with lower urinary tract symptoms (LUTS) attributed to benign prostatic hyperplasia. Salvage robotic simple prostatectomy (SSP) is defined as simple prostatectomy after failed transurethral procedure. The aim of this study is to evaluate the efficacy of primary robotic simple prostatectomy (PSP) SSP in ameliora...

Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients.

Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatment response for glioblastoma. This assessment is, however, complex to perform and associated with high variability due to the high heterogeneity and complexity of the disease. In this work, we tackle this issue and propose a deep learning pipeline for the fully automated end-to-end analysis of gliobl...

Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes.

Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are supported by 'contextual explanations' that let the pract...

Artificial Intelligence and Data Mining for the Pharmacovigilance of Drug-Drug Interactions.

Despite increasing mechanistic understanding, undetected and underrecognized drug-drug interactions (DDIs) persist. This elusiveness relates to an int...

Localization and quantification of glottal gaps on deep learning segmentation of vocal folds.

The entire glottis has mostly been the focus in the tracking of the vocal folds, both manually and automatically. From a treatment point of view, the ...

Using Deep Learning to Predict Treatment Response in Patients with Hepatocellular Carcinoma Treated with Y90 Radiation Segmentectomy.

Treatment of hepatocellular carcinoma (HCC) with Y90 radioembolization segmentectomy (Y90-RE) demonstrates a tumor dose-response threshold, where dose...

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era.

At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting C...

Exploratory pharmacovigilance with machine learning in big patient data: A focused scoping review.

BACKGROUND: Machine learning can operationalize the rich and complex data in electronic patient records for exploratory pharmacovigilance endeavours.

Adverse drug event detection using natural language processing: A scoping review of supervised learning methods.

To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural l...

LiSA: an assisted literature search pipeline for detecting serious adverse drug events with deep learning.

INTRODUCTION: Detecting safety signals attributed to a drug in scientific literature is a fundamental issue in pharmacovigilance. The constant increas...

Prediction and interpretation of antibiotic-resistance genes occurrence at recreational beaches using machine learning models.

Antibiotic-resistant bacteria and antibiotic resistance genes (ARGs) are pollutants of worldwide concern that seriously threaten public health and eco...

Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions.

The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an inciden...

What place for intelligent automation and artificial intelligence to preserve and strengthen vigilance expertise in the face of increasing declarations?

In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI) and led its experts to confirm the potential con...

The effect of an interactive robot on children's post-operative anxiety, mobilization, and parents' satisfaction; randomized controlled study.

PURPOSE: To evaluate the effect of an interactive robot on Turkish children's post-operative anxiety, mobilization, and parents' satisfaction related ...

A novel soft robotic pediatric in vitro swallowing device to gain insights into the swallowability of mini-tablets.

Soft robotics could help providing a better understanding of the mechanisms underpinning the swallowability of solid oral dosage forms (SODF), especia...

A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal.

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with autom...

Deep Learning for Image Enhancement and Correction in Magnetic Resonance Imaging-State-of-the-Art and Challenges.

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical diagnoses and research which underpin many recent breakthroughs ...

Diaphragmatic paralysis post COVID-19 treated with robot-assisted plication reinforced with acellular dermal matrix: a report of two cases.

Coronavirus disease 2019 (COVID-19) continues to be a disease of global importance, with an increasing array of sequelae attributed to infection by th...

SkiNet: A deep learning framework for skin lesion diagnosis with uncertainty estimation and explainability.

Skin cancer is considered to be the most common human malignancy. Around 5 million new cases of skin cancer are recorded in the United States annually...

Feasibility of transthoracic esophagectomy with a next-generation surgical robot.

Robot-assisted minimal access surgery (MAS), compared with conventional MAS, has shown a number of benefits across several therapeutic indications but...