机器学习技术在食管癌研究领域中应用的现状与展望

Current situation and prospects of machine learning applications in the study of esophageal cancer

我国是世界上食管癌的高发国家之一。食管癌的早期发现与准确诊疗对提高患者的预后与生存具有重要意义。随着医学影像的积累和人工智能技术的进步,机器学习技术在癌症中被广泛应用。本文归纳了目前机器学习技术在食管癌基础研究和临床诊断中所用到的学习模型、图像类型、数据类型与应用效率;探讨了目前食管癌医学图像机器学习的主要困境和解决方法;讨论了未来机器学习在食管癌诊疗中可能的方向,特别是建立医学图像与分子机制间联系的可能。在此基础上,对机器学习在医学领域应用的一般规律进行了总结与展望。通过借鉴机器学习在其它癌症中的先进成果,注重多学科交叉合作,将有效促进食管癌研究的发展。

China is one of the countries in the world with the highest rate of esophageal cancer.Early detection,accurate diagnosis,and treatment of esophageal cancer are critical for improving patients’prognosis and survival.Machine learning technology has become widely used in cancer,which is benefited from the accumulation of medical images and advancement of artificial intelligence technology.Therefore,the learning model,image type,data type and application efficiency of current machine learning technology in esophageal cancer are summarized in this review.The major challenges are identified,and solutions are proposed in medical image machine learning for esophageal cancer.Machine learning's potential future directions in esophageal cancer diagnosis and treatment are discussed,with a focus on the possibility of establishing a link between medical images and molecular mechanisms.The general rules of machine learning application in the medical field are summarized and forecasted on this foundation.By drawing on the advanced achievements of machine learning in other cancers and focusing on interdisciplinary cooperation,esophageal cancer research will be effectively promoted.