Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning

With the wider adoption of electronic health records, the rapid response team initially believed that mortalities could be significantly reduced but due to low accuracy and false alarms, the healthcare system is currently fraught with many challenges. Rule-based methods (e.g., Modified Early Warning Score) and machine learning (e.g., random forest) were proposed as a solution but not effective. In this article, we introduce the DeepEWS (Deep learning based Early Warning Score), which is based on a novel deep learning algorithm. Relative to the standard of care and current solutions in the marketplace, there is high accuracy, and in the clinical setting even when we consider the number of alarms, the accuracy levels are superior

Validation of deep-learning-based triage and acuity score using a large national dataset.

AIM:Triage is important in identifying high-risk patients amongst many less urgent patients as emergency department (ED) overcrowding has become a national crisis recently. This study aims to validate that a Deep-learning-based Triage and Acuity Score (DTAS) identifies high-risk patients more accurately than existing triage and acuity scores using a large national dataset. METHODS:We conducted a retrospective observational cohort study using data from the Korean National Emergency Department Information System (NEDIS), which collected data on visits in real time from 151 EDs. The NEDIS data was split into derivation data (January 2014-June 2016) and validation data (July-December 2016). We also used data from the Sejong General Hospital (SGH) for external validation (January-December 2017). We predicted in-hospital mortality, critical care, and hospitalization using initial information of ED patients (age, sex, chief complaint, time from symptom onset to ED visit, arrival mode, trauma, initial vital signs and mental status as predictor variables). RESULTS:A total of 11,656,559 patients were included in this study. The primary outcome was in-hospital mortality. The Area Under the Receiver Operating Characteristic curve (AUROC) and Area Under the Precision and Recall Curve (AUPRC) of DTAS were 0.935 and 0.264. It significantly outperformed Korean triage and acuity score (AUROC:0.785, AUPRC:0.192), modified early warning score (AUROC:0.810, AUPRC:0.116), logistic regression (AUROC:0.903, AUPRC:0.209), and random forest (AUROC:0.910, AUPRC:0.179). CONCLUSION:Deep-learning-based Triage and Acuity Score predicted in-hospital mortality, critical care, and hospitalization more accurately than existing triages and acuity, and it was validated using a large, multicenter dataset

Nitric oxide-releasing polymer incorporated ointment for cutaneous wound healing

This work demonstrates the development of nitric oxide-releasing ointment and its potential on efficient wound healing. Nitric oxide-releasing polymer was successfully synthesized, which is composed of biocompatible Pluronic F127, branched polyethylenimine and 1-substituted diazen-1-ium-1,2-diolates. The synthesized nitric oxide-releasing polymer was incorporated into the PEG-based ointment which not only facilitated nitric oxide release in a slow manner, but also served as a moisturizer to enhance the wound healing. As compared to control groups, the nitric oxide-releasing ointment showed the accelerated wound closure with enhanced re-epithelialization, collagen deposition, and blood vessel formation in vivo. Therefore, this nitric oxide-based ointment presents the promising potential for the efficient strategy to heal the cutaneous wound. © 2015 Elsevier B.V. All rights reserved117181sciescopu

Evaluation of a rapid immunodiagnostic test kit for rabies virus

A rapid immunodiagnostic test kit for rabies virus detection was evaluated using 51 clinical samples and 4 isolates of rabies virus. The quick detection of rabies virus under field conditions may be helpful in determining if post-exposure prophylaxis is needed, thereby avoiding unnecessary treatments, as well as undue economic burden. There are several widely used diagnostic methods for rabies, including fluorescent antibody tests, reverse transcription polymerase chain reaction, and electron microscopy; however, these methods include time-consuming, intricate, and costly procedures. The rapid immunodiagnostic test was able to detect rabies virus in clinical samples, including brain tissue and saliva, in addition to 103.2 50% lethal dose (LD50)/mL cell-adapted rabies virus. The assay was not cross-reactive with non-rabies virus microbes. When the performance of the rapid immunodiagnostic test was compared to a fluorescent antibody test, the rapid immunodiagnostic test had a sensitivity of 91.7% and specificity of 100% (95.8% CI)

Development of a Multiplex Reverse Transcription-Polymerase Chain Reaction Assay for the Simultaneous Detection of Three Viruses in Leguminous Plants

A multiplex reverse transcription-polymerase chain reaction (mRT-PCR) assay was developed for the detection of Clover yellow vein virus (ClYVV), Peanut mottle virus (PeMoV), and Tomato spotted wilt virus (TSWV), which were recently reported to infect soybean and azuki bean in Korea. Species-specific primer sets were designed for the detection of each virus, and their specificity and sensitivity were tested using mixed primer sets. From among the designed primer sets, two combinations were selected and further evaluated to estimate the detection limits of uniplex, duplex, and multiplex RT-PCR. The multiplex RT-PCR assay could be a useful tool for the field survey of plant viruses and the rapid detection of ClYVV, PeMoV, and TSWV in leguminous plants