Exarchos Konstantinos P, Gkrepi Georgia, Kostikas Konstantinos, Gogali Athena
Respiratory Medicine Department, University of Ioannina School of Medicine, 45110 Ioannina, Greece.
Diagnostics (Basel). 2023 Jul 6;13(13):2303. doi: 10.3390/diagnostics13132303.
Interstitial lung diseases (ILDs) comprise a rather heterogeneous group of diseases varying in pathophysiology, presentation, epidemiology, diagnosis, treatment and prognosis. Even though they have been recognized for several years, there are still areas of research debate. In the majority of ILDs, imaging modalities and especially high-resolution Computed Tomography (CT) scans have been the cornerstone in patient diagnostic approach and follow-up. The intricate nature of ILDs and the accompanying data have led to an increasing adoption of artificial intelligence (AI) techniques, primarily on imaging data but also in genetic data, spirometry and lung diffusion, among others. In this literature review, we describe the most prominent applications of AI in ILDs presented approximately within the last five years. We roughly stratify these studies in three categories, namely: (i) screening, (ii) diagnosis and classification, (iii) prognosis.
间质性肺疾病（ILDs）是一组病理生理学、临床表现、流行病学、诊断、治疗及预后各异的相当异质性疾病。尽管它们已被认识多年，但仍存在研究争议领域。在大多数ILD中，影像学检查方法，尤其是高分辨率计算机断层扫描（CT）已成为患者诊断方法及随访的基石。ILD的复杂性及相关数据促使人工智能（AI）技术的应用日益增加，主要应用于影像数据，也包括基因数据、肺功能测定及肺弥散功能等。在这篇文献综述中，我们描述了过去五年左右AI在ILD中最突出的应用。我们大致将这些研究分为三类，即：（i）筛查，（ii）诊断与分类，（iii）预后。
