Artificial Intelligence In Pulmonary Diseases
Özet
Artificial intelligence (AI) and machine learning (ML) are driving a transformative era in healthcare, particularly within pulmonary medicine. By leveraging big data from medical records, physiological testing, and advanced imaging modalities, AI algorithms are significantly enhancing diagnostic efficiency, accuracy, and overall clinical workflow management. In pulmonology, AI applications have demonstrated outstanding capabilities across various domains. Specifically, deep learning algorithms using convolutional neural networks optimize thoracic imaging by accelerating report turnaround times and improving the detection of malignant pulmonary nodules and tuberculosis on chest X-rays. Furthermore, AI-based software assists in the interpretation of standard pulmonary function tests (PFTs), outperforming specialists by providing consistent, data-driven decisions for heterogeneous conditions like chronic obstructive pulmonary disease (COPD) and asthma. Beyond diagnostics, AI integration transforms histopathology by enabling accurate differential diagnoses with minimal tissue samples, and powers telemedicine via predictive smartphone telemonitoring for disease exacerbations. During the COVID-19 pandemic, AI proved crucial for early recognition, treatment monitoring, and rapid vaccine development. As digitalized medical big data continues to accumulate globally, the sensitivity and precision of these intelligent systems will further expand, guiding pulmonary clinical practice into an unprecedented era of augmented medicine.
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