RESUMO
We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities. This dataset and respective annotations are available to researchers for academic and noncommercial use.
Assuntos
COVID-19 , Humanos , Inteligência Artificial , Radiografia , Aprendizado de Máquina , Radiologistas , Radiografia Torácica/métodosRESUMO
Due to recent advances in artificial intelligence, there is renewed interest in automating interpretation of imaging tests. Chest radiographs are particularly interesting due to many factors: relatively inexpensive equipment, importance to public health, commonly performed throughout the world, and deceptively complex taking years to master. This article presents a brief introduction to artificial intelligence, reviews the progress to date in chest radiograph interpretation, and provides a snapshot of the available datasets and algorithms available to chest radiograph researchers. Finally, the limitations of artificial intelligence with respect to interpretation of imaging studies are discussed.
Assuntos
Inteligência Artificial/tendências , Radiografia Torácica/tendências , Algoritmos , Diagnóstico por Computador/tendências , Previsões , Humanos , Pneumopatias/diagnóstico por imagem , Aprendizado de Máquina/tendências , Radiografia Torácica/métodos , Tuberculose Pulmonar/diagnóstico por imagemRESUMO
The 1990s are presenting new challenges to hospital CEOs. One theme currently emerging is the ethics of resource allocation. As they search for ways to fulfill their community responsibilities under pressures related to reimbursement, technology and community desires, hospitals are finding that they must make some very tough choices in how they allocate resources. Given the opportunity, how would you respond? Compare your response to an ethical scenario with those of three nationally recognized hospital CEOs.
