Machine learning and big data in precision medicine: what is the role of the Radiologist?

Giovanni MORANA
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Abstract

With the advent of artificial intelligence (AI) in the field of radiology, a new perspective opens up in terms of diagnosis and management of patients. There is a need to review the way radiologists work so as to rebuild the doctor-patient relationship that has been sidelined over the years to increase our productivity. It is precisely the improvement in productivity that will be made possible by AI that will be able to free the radiology physician from time-consuming activities that add little to the diagnostic value of our work; this “gift of time” will have to be used to have a direct relationship with the patient, who can be followed up directly by the radiology physician, and not just sent by other physicians. This will be all the more necessary since with the new methods of image analysis (deep learning, texture analysis) the radiologist physician will not only have the task of diagnosing a lesion as accurately as possible, but also of indicating its evolution and progression, what makes indispensable a new pact with the patient, who will have to not only “accept” the diagnosis of an existing lesion but, above all, will have to trust the prognosis of that lesion, a trust based on an immaterial datum (the advanced image analysis) but which weighs like a boulder on the psyche of the patient. Only a relationship of great trust with his new physician, the radiologist, can make him follow our directions.
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精准医疗中的机器学习和大数据:放射科医生的角色是什么?
随着人工智能(AI)在放射学领域的出现,为患者的诊断和管理开辟了新的视角。有必要重新审视放射科医生的工作方式,以便重建多年来被搁置的医患关系,以提高我们的工作效率。人工智能将使生产力的提高成为可能,它将使放射科医生从耗时的活动中解放出来,这些活动对我们的工作的诊断价值几乎没有贡献;这种“时间的礼物”必须用来与病人建立直接的关系,病人可以由放射科医生直接随访,而不仅仅是由其他医生发送。这将是更加必要的,因为有了新的图像分析方法(深度学习,纹理分析),放射科医生不仅要尽可能准确地诊断病变,而且要表明其演变和进展,这使得与患者达成新的协议变得必不可少,患者不仅要“接受”现有病变的诊断,而且最重要的是,必须相信病变的预后。这是一种基于非物质数据(高级图像分析)的信任,但对患者的精神来说,它就像一块巨石。只有与他的新医生——放射科医生建立起高度信任的关系,才能使他听从我们的指示。
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