scholarly journals Deep learning for classification of pediatric chest radiographs by WHO’s standardized methodology

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253239
Author(s):  
Yiyun Chen ◽  
Craig S. Roberts ◽  
Wanmei Ou ◽  
Tanaz Petigara ◽  
Gregory V. Goldmacher ◽  
...  
Keyword(s):  
Deep Learning ◽  
World Health Organization ◽  
Characteristic Curve ◽  
Learning Model ◽  
Observer Agreement ◽  
World Health ◽  
Widespread Application ◽  
The World ◽  
Health Organization ◽  
Deep Learning Model

Background The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of this endpoint. Methods We trained a deep learning model to classify pneumonia CXRs in children using the World Health Organization (WHO)’s standardized methodology. The model was pretrained on CheXpert, a dataset containing 224,316 adult CXRs, and fine-tuned on PERCH, a pediatric dataset containing 4,172 CXRs. The model was then tested on two pediatric CXR datasets released by WHO. We also compared the model’s performance to that of radiologists and pediatricians. Results The average area under the receiver operating characteristic curve (AUC) for primary endpoint pneumonia (PEP) across 10-fold validation of PERCH images was 0.928; average AUC after testing on WHO images was 0.977. The model’s classification performance was better on test images with high inter-observer agreement; however, the model still outperformed human assessments in AUC and precision-recall spaces on low agreement images. Conclusion A deep learning model can classify pneumonia CXR images in children at a performance comparable to human readers. Our method lays a strong foundation for the potential inclusion of computer-aided readings of pediatric CXRs in vaccine trials and epidemiology studies.

scholarly journals Worldwide and Regional Forecasting of Coronavirus (Covid-19) Spread using a Deep Learning Model

2020 ◽  
Author(s):  
Cem Direkoglu ◽  
Melike Sah
Keyword(s):  
Deep Learning ◽  
Middle East ◽  
World Health Organization ◽  
Time Series Data ◽  
Learning Model ◽  
World Health ◽  
Series Data ◽  
Cumulative Number ◽  
Health Organization ◽  
Deep Learning Model

AbstractIn December 2019, Covid-19 epidemic was identified in Wuhan, China. Covid-19 may cause fatality especially among elderly, and people with chronic health problems. After human to human transmissions of the disease, it has rapidly spread throughout China, and then the outbreak has reached to neighboring countries in Asia. Now, the spread of the virus is accelerating in the world, and increasing number of new cases has been reported daily in Europe, Middle East, Africa and America regions. Recently, World Health Organization (WHO) also announced Covid-19 as a Pandemic. As of 3 April, worldwide around more than 1 million cases and around 60,000 fatalities are reported. Thus, forecasting regional and worldwide outbreak size of Covid-19 is important in order to take necessary actions regarding to preparedness plans and mitigation interventions. In this work, we design a deep learning model, which is an effective artificial intelligence method, to provide regional and worldwide forecasts. Particularly for worldwide, our approach predicts the cumulative number of cases, cumulative number of deaths and daily new cases. For Europe and Middle East regions, we predict the cumulative number of cases, and for Mainland China we predict daily new cases and the cumulative number of deaths. We predict the next 10 days based on the previously reported actual time series data of Covid-19. For worldwide forecasts, we use the data provided by Worldometers. For Europe and Middle East forecasts, we use the data provided by World Health Organization, and for China Mainland forecasts, the data is obtained from Chinese Centre for Disease Control and Prevention. This is the first time that a deep learning model has been employed for Covid-19 spread prediction, solely based on the known reported cases of Covid-19. The proposed deep learning architecture consists of Long Short Term Memory (LSTM) layer, dropout layer, and fully connected layers to predict regional and worldwide forecasts. We evaluate our approach with Root Mean Square Error (RMSE) metric. For forecasting, we use the network models that give the minimum RMSE on the last 3 days of actual data. Networks, which achieves the minimum RMSE on the last 3 days, are used to predict the next 10 days. Every day, the spread and situations are changing. Our approach can take into account these realtime changes; the deep learning model can be re-trained with new daily data and perform real-time forecasting. Results show that the proposed deep learning model is promising, it can predict possible scenarios regionally and globally for the spread of Covid-19.

Erstes Instrument zur standardisierten Erfassung der Teilhabe Behinderter

2017 ◽  
Vol 79 (07) ◽  
pp. 526-527
Keyword(s):  
World Health Organization ◽  
World Health ◽  
The World ◽  
Health Organization ◽  
Menschen Mit Behinderung

Coenen M et al. [Recommendation for the collection and analysis of data on participation and disability from the perspective of the World Health Organization]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2016; 59: 1060–1067 Um eine gleichberechtigte Teilhabe an der Gesellschaft von Menschen mit Behinderung zu ermöglichen, werden zunächst Daten zu vorhandenen Einschränkungen gebraucht. Erst wenn diese detailliert erhoben wurden, können Konzepte zur Beseitigung von Problemen entwickelt werden. Ein standardisiertes Erhebungsinstrument für alle Aspekte der Funktionsfähigkeit fehlte jedoch bisher.

Recomendações de equipamentos de proteção individual no combate ao COVID-19

2020 ◽  
Vol 10 (31) ◽  
pp. 87-95
Author(s):  
Nicole Maria Miyamoto Bettini ◽  
Fabiana Tomé Ramos ◽  
Priscila Masquetto Vieira de Almeida
Keyword(s):  
World Health Organization ◽  
Personal Protective Equipment ◽  
Health Professionals ◽  
Health Personnel ◽  
Healthcare Professionals ◽  
World Health ◽  
Protective Equipment ◽  
Effective Strategy ◽  
The World ◽  
Health Organization

A Organização Mundial da Saúde - OMS confirmou a circulação internacional do novo Coronavírus em janeiro de 2020, nomeando-o como COVID-19 e, declarando uma pandemia. É de extrema importância que durante a pandemia, os profissionais de saúde tenham acesso e conhecimento sobre o uso correto dos Equipamentos de Proteção Individual (EPIs) e suas indicações, tomando assim, as devidas precauções na prevenção de infecções. O presente estudo buscou identificar a padronização mundial quanto ao uso dos EPIs utilizados no atendimento a pacientes suspeitos e/ou confirmados de COVID-19 no Brasil, EUA, China, Espanha, Itália e demais países europeus. Os guidelines apresentam a padronização quanto ao uso dos EPIs utilizados no atendimento a suspeitos e/ou confirmados de COVID-19, indo ao encontro das recomendações fornecidas pela OMS. Até o momento, o uso de EPIs é sem dúvida a estratégia mais importante e eficaz para proteger os profissionais de saúde durante a assistência ao paciente com COVID-19.Descritores: Infecções por Coronavírus, Equipamento de Proteção Individual, Pessoal de Saúde, Enfermagem. Recommendations for personal protective equipment to combat COVID-19Abstract: The World Health Organization - WHO confirmed the international circulation of the new Coronavirus in January 2020, naming it as COVID-19 and declaring a pandemic. It is extremely important that during the pandemic, health professionals have access and knowledge about the correct use of Personal Protective Equipment (PPE) and its indications, thus taking appropriate precautions to prevent infections. The present study sought to identify the worldwide standardization regarding the use of PPE utilized to take care of suspected and confirmed patients with COVID-19 in Brazil, USA, China, Spain, Italy and other European countries. The guidelines present a standardization regarding the use of PPE utilized to take care of suspected and confirmed with COVID-19, in line with the recommendations provided by WHO. To date, the use of PPE is undoubtedly the most important and effective strategy to protect healthcare professionals during care for patients with COVID-19.Descriptors: Coronavirus Infections, Personal Protective Equipment, Health Personnel, Nursing. Recomendaciones para el equipo de protección personal para combatir COVID-19Resumen: La Organización Mundial de la Salud - La OMS confirmó la circulación internacional del nuevo Coronavirus en enero de 2020, nombrándolo COVID-19 y declarando una pandemia. Es extremadamente importante que durante la pandemia, los profesionales de la salud tengan acceso y conocimiento sobre el uso correcto del Equipo de Protección Personal (EPP) y sus indicaciones, tomando así las precauciones adecuadas para prevenir infecciones. El presente estudio buscó identificar la estandarización mundial con respecto al uso de EPP utilizado para atender a pacientes sospechosos y/o confirmados con COVID-19 en Brasil, Estados Unidos, China, España, Italia y otros países europeos. Las pautas presentan la estandarización con respecto al uso de EPP utilizado para cuidar COVID-19 sospechoso y/o confirmado, de acuerdo con las recomendaciones proporcionadas por la OMS. Hasta la fecha, el uso de EPP es, sin duda, la estrategia más importante y efectiva para proteger a los profesionales de la salud durante la atención de pacientes con COVID-19.Descriptores: Infecciones por Coronavirus, Equipo de Protección Personal, Personal de Salud, Enfermería.

Current updates on COVID-19 - A review

2020 ◽  
Vol 10 (1) ◽  
pp. 1-8
Author(s):  
Ghotekar D S ◽  
Vishal N Kushare ◽  
Sagar V Ghotekar
Keyword(s):  
World Health Organization ◽  
Common Cold ◽  
Respiratory Diseases ◽  
Gastrointestinal Diseases ◽  
Hubei Province ◽  
World Health ◽  
The World ◽  
The Common ◽  
Novel Coronavirus ◽  
Health Organization

Coronaviruses are a family of viruses that cause illness such as respiratory diseases or gastrointestinal diseases. Respiratory diseases can range from the common cold to more severe diseases. A novel coronavirus outbreak was first documented in Wuhan, Hubei Province, China in December 2019. The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) a pandemic. A global coordinated effort is needed to stop the further spread of the virus. A novel coronavirus (nCoV) is a new strain that has not been identified in humans previously. Once scientists determine exactly what coronavirus it is, they give it a name (as in the case of COVID-19, the virus causing it is SARS-CoV-2).

Sign in / Sign up

Export Citation Format

Share Document