Publications by authors named "Deokjae Han"

The computer-aided diagnosis (CAD) for chest X-rays was developed more than 50 years ago. However, there are still unmet needs for its versatile use in our medical fields. We planned this study to develop a multipotent CAD model suitable for general use including in primary care areas.

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Purpose: We previously developed learning models for predicting the need for intensive care and oxygen among patients with coronavirus disease (COVID-19). Here, we aimed to prospectively validate the accuracy of these models.

Materials And Methods: Probabilities of the need for intensive care [intensive care unit (ICU) score] and oxygen (oxygen score) were calculated from information provided by hospitalized COVID-19 patients (n=44) via a web-based application.

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Background/aims: Acute eosinophilic pneumonia (AEP) is common among military smokers; however, bronchoscopy is required for the diagnosis. We aimed to derive and validate a scoring system to diagnose AEP without bronchoscopy.

Methods: We conducted a retrospective study including patients diagnosed with AEP or any other pneumonia among military smokers hospitalized in the Armed Forces Capital Hospital from 15 November 2016 through 25 December 2019.

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Article Synopsis
  • A study was conducted to create and validate a scoring system that predicts COVID-19 patients who might need intensive care, using data available when patients are first assessed.
  • The research analyzed patient data from South Korea's CDC, focusing on those admitted between January and June 2020, with the aim of prioritizing hospital resources to reduce fatalities.
  • The final scoring system incorporates seven clinical factors—like age, sex, and specific symptoms—and demonstrated strong predictive performance, performing well even without additional lab or imaging data.
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Article Synopsis
  • The study aimed to create a machine learning model to predict which COVID-19 patients would need intensive care using simple data like demographics, health conditions, and symptoms, rather than complex tests that might be hard to access.
  • Researchers collected data from nearly 5,000 patients across 100 hospitals in South Korea during early 2020, dividing them into groups for developing and validating the prediction model.
  • The best prediction model showed strong performance in identifying patients needing intensive care and was compared with an existing score (CURB-65), demonstrating its effectiveness in real-world scenarios.
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Background: Clear guidelines for a patient with suspected COVID-19 infection are unavailable. Many countries rely on assessments through a national hotline or telecommunications, but this only adds to the burden of an already overwhelmed health care system. In this study, we developed an algorithm and a web application to help patients get screened.

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Background: COVID-19 has officially been declared as a pandemic, and the spread of the virus is placing sustained demands on public health systems. There are speculations that the COVID-19 mortality differences between regions are due to the disparities in the availability of medical resources. Therefore, the selection of patients for diagnosis and treatment is essential in this situation.

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Background: Little clinical information on high grade tuberculosis destroyed lung (TDL) is available. The aim of this study was to investigate the characteristics and healthcare utilization of high grade TDL patients, and compared the differences between acute exacerbation and healthcare burden according to inhaler compliance.

Methods: This was an observational retrospective cohort study using the Korean Health Insurance Review and Assessment (HIRA) service database (2011-2015).

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Background: Pulmonary capillary hemangiomatosis (PCH) is a progressive and refractory vascular disease in the lung. Pulmonary hypertension is frequently combined with PCH when capillary proliferation invades to nearby pulmonary vascular systems. It is difficult to differentiate PCH from other diseases such as pulmonary venoocclusive disease and pulmonary arterial hypertension that cause pulmonary hypertension as they frequently overlap.

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Background: Roflumilast is the only approved oral phosphodiesterase-4 inhibitor for the treatment of severe chronic obstructive pulmonary disease (COPD) in patients with chronic bronchitis and a history of frequent exacerbations. The purpose of this study was to examine the incidence of adverse effects associated with roflumilast treatment in a real-world setting. Further, we compared the incidence of adverse effects and the discontinuation rate among patients receiving different doses.

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Many patients suffering from asthma or COPD have overlapping features of both diseases. However, a phenotypical approach for evaluating asthma-COPD overlap syndrome (ACOS) has not been established. In this report, we examined the phenotypes in patients with ACOS.

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