数字化病理学
步伐
心灵感应学
计算机科学
病理
解剖病理学
医学
数据科学
医学物理学
医疗保健
远程医疗
政治学
大地测量学
法学
免疫组织化学
地理
作者
Jorge S. Reis‐Filho,Jakob Nikolas Kather
摘要
Abstract Pathologists worldwide are facing remarkable challenges with increasing workloads and lack of time to provide consistently high-quality patient care. The application of artificial intelligence (AI) to digital whole-slide images has the potential of democratizing the access to expert pathology and affordable biomarkers by supporting pathologists in the provision of timely and accurate diagnosis as well as supporting oncologists by directly extracting prognostic and predictive biomarkers from tissue slides. The long-awaited adoption of AI in pathology, however, has not materialized, and the transformation of pathology is happening at a much slower pace than that observed in other fields (eg, radiology). Here, we provide a critical summary of the developments in digital and computational pathology in the last 10 years, outline key hurdles and ways to overcome them, and provide a perspective for AI-supported precision oncology in the future.
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