Quantitative evaluation model of variable diagnosis for chest X-ray images using deep learning.

The purpose of this study is to demonstrate the use of a deep learning model in quantitatively evaluating clinical findings typically subject to uncertain evaluations by physicians, using binary test results based on routine protocols. A chest X-ray is the most commonly used diagnostic tool for the detection of a wide range of diseases and is generally performed as a part of regular medical checkups. However, when it comes to findings that can be classified as within the normal range but are not considered disease-related, the thresholds of physicians' findings can vary to some extent, therefore it is necessary to define a new evaluation method and quantify it.

Pleural thickening on screening chest X-rays: a single institutional study.

Although pleural thickening is a common finding on routine chest X-rays, its radiological and clinical features remain poorly characterized. Our investigation of 28,727 chest X-rays obtained from annual health examinations confirmed that pleural thickening was the most common abnormal radiological finding. In most cases (92.

The incidence and risk factors of asymptomatic primary spontaneous pneumothorax detected during health check-ups.

Background: Patients with primary spontaneous pneumothorax (PSP) usually complain of sudden-onset dyspnea and pleuritic chest pain. However, asymptomatic PSP has been incidentally detected on chest X-rays. In this study, we analyzed the incidence, characteristics, risk factors, and prognosis of asymptomatic PSP detected during regular medical check-ups in university students.