Prevention of medical errors

Safety and Efficacy of Tolvaptan for the Prevention of Contrast-Induced Acute Kidney Injury in Patients with Heart Failure and Chronic Kidney Disease.

BACKGROUND: Tolvaptan is a promising drug for the prevention of contrast-induced acute kidney injury (CI-AKI) because it induces aquaresis without adversely affecting renal hemodynamics. CI-AKI is a major cause of acute renal failure associated with increased morbidity and mortality.

Toward Automatic Risk Assessment to Support Suicide Prevention.

Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide risk has proven extremely difficult to assess for medical specialists, and traditional methodologies deployed have been ineffective. Advances in machine...

A Randomized Control Trial Of Anti-Inflammatory Regional Hypothermia On Urinary Continence During Robot-Assisted Radical Prostatectomy.

The present study seeks to present a single-blind, randomized control trial of a hypothermic anti-inflammatory device, the endorectal cooling balloon ...

Risky Business: Judging the Use of Non-Vitamin K Antagonist Oral Anticoagulants for Non-Valvular Atrial Fibrillation in Patients with Renal Dysfunction.

Warfarin, for many years, was the only oral anticoagulant availablt on the market for the prevention of stroke in patients with atrial fibrillation. D...

A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning.

Computer aided diagnosis (CAD) tools help radiologists to reduce diagnostic errors such as missing tumors and misdiagnosis. Vision researchers have be...

A Machine Learning Approach to Identify NIH-Funded Applied Prevention Research.

INTRODUCTION: To fulfill its mission, the NIH Office of Disease Prevention systematically monitors NIH investments in applied prevention research. Spe...

Aiding the Digital Mammogram for Detecting the Breast Cancer Using Shearlet Transform and Neural Network.

Objective: Breast Cancer is the most invasive disease and fatal disease next to lung cancer in human. Early detection of breast cancer is accomplished...

Digital diabetes: Perspectives for diabetes prevention, management and research.

Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden re...

A robotic system to prepare IV solutions.

Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly, negativities that threaten human health and...

UKF-based remote state estimation for discrete artificial neural networks with communication bandwidth constraints.

This paper is concerned with the remote state estimator design problem for a class of discrete neural networks under communication bandwidth constrain...

Telemedicine and telerobotics: from science fiction to reality.

Advances in communication technologies have paved the way for telemedicine to transform the delivery of medical care throughout the world. Coinciding ...

Sum Rate of MISO Neuro-Spike Communication Channel With Constant Spiking Threshold.

Communication among neurons, known as neuro-spike communication, is the most promising technique for realization of a bio-inspired nanoscale communica...

Event-triggered H state estimation for semi-Markov jumping discrete-time neural networks with quantization.

This paper investigates H state estimation problem for a class of semi-Markovian jumping discrete-time neural networks model with event-triggered sche...

Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Very little is known about the health problems experienced by individuals with autism spectrum disorder (ASD) throughout their life course. We retrosp...

Identifying β-thalassemia carriers using a data mining approach: The case of the Gaza Strip, Palestine.

Thalassemia is considered one of the most common genetic blood disorders that has received excessive attention in the medical research fields worldwid...

Robot Assisted Surgical Ward Rounds: Virtually Always There.

 While an explosion in technological sophistication has revolutionized surgery within the operating theatre, delivery of surgical ward-based care has ...

Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access.

BACKGROUND: On December 6 and 7, 2017, the US Department of Health and Human Services (HHS) hosted its first Code-a-Thon event aimed at leveraging tec...

Inferring Clinical Correlations from EEG Reports with Deep Neural Learning.

Successful diagnosis and management of neurological dysfunction relies on proper communication between the neurologist and the primary physician (or o...

Structure-function properties of hypolipidemic peptides.

This review addresses the structure-function properties of hypolipidemic peptides. The cholesterol-lowering peptide (lactostatin: IIAEK) operates via ...

A modified artificial neural network based prediction technique for tropospheric radio refractivity.

Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity i...