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Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remains opaque. This makes it difficult for humans to validate a prediction made by AI against their own domain knowledge.

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Background: The rise of low-dose computed tomography (LDCT) has increased the detection of small pulmonary nodules, demanding more effective localization techniques for their resection. Minimally invasive resection utilizing video-assisted thoracoscopic surgery (VATS) is a critical method for treating these nodules. However, traditional computed tomography (CT)-guided localization has limitations such as invasiveness and patient discomfort.

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Mature cystic teratomas exhibit a variety of tissues within their pathology. In adults, teratomas typically originate in the gonads. However, one of the rarest origins is the lung, making intrapulmonary teratoma (IPT) exceedingly uncommon.

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Aplasia of the lung is an uncommon congenital anomaly that can resemble several common illnesses radiologically and presents as an opaque hemithorax with ipsilateral displacement of the mediastinum. This case scenario involves a young woman who has been experiencing recurrent pulmonary tract infections and worsening dyspnea since childhood, presenting as pneumonic consolidation on a chest X-ray. The case explores the importance of lung scans, CT pulmonary angiography, and bronchoscopy to elicit the absence of lung parenchyma on one side.

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Objective: During the COVID-19 pandemic, universal mask-wearing became one of the main public health interventions. Because of this, most physical examinations, including lung auscultation, were done while patients were wearing surgical face masks. The aim of this study was to investigate whether mask wearing has an impact on pulmonologist assessment during auscultation of the lungs.

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