Lancet Oncol:用于诊断皮肤病变的人工智能

2019-07-13 佚名 中国生物技术网

近日,在维也纳医学大学领导的一项研究中,人类皮肤病专家与计算机算法竞赛。后者取得了更好的结果,但它们目前的能力还无法取代人类。该研究结果近日已发表在《The Lancet Oncology》上。

21世纪医学的最大进步将是在分子生物学突破的基础上,精准医学的成熟及人工智能渗透到医学的各个领域。近日,在维也纳医学大学领导的一项研究中,人类皮肤病专家与计算机算法竞赛。后者取得了更好的结果,但它们目前的能力还无法取代人类。该研究结果近日已发表在《The Lancet Oncology》上。



国际皮肤影像协作组织(ISIC)和维也纳医学大学组织了一次挑战,将511名医生的诊断结果与来自77个不同的机器学习实验室的139种算法进行比较。这些实验室参与了国际皮肤成像协作2018年的挑战,并提前收到了10015个图像的数据库。该数据库由维也纳MedUni皮肤病学系的Harald Kittler团队与澳大利亚昆士兰大学合作建立。

数据库中包括良性(痣、日晒斑、老年疣、血管瘤和皮肤纤维瘤)和恶性色素沉着病变(黑色素瘤、基底细胞癌和色素性鳞状细胞癌)。

每个参与的医生要求从1511幅图像中随机选择30幅图像进行诊断。结果很明显,在30个病例中,成绩最好的医生正确诊断了18.8个病例,而成绩最高的机器得到了25.4个正确诊断。





该研究第一作者、维也纳医学大学的Philipp Tschandl博士说:“这并不令我感到惊讶。所有参与的机器中有三分之二比人类更好,这一结果在过去几年的类似试验中已经得到证实。”

不能取代人类

虽然在这个实验中算法明显优于人类,但这并不意味着在皮肤癌的诊断中机器将取代人类。Tschandl说:“计算机非常适合分析光学快照。但在现实生活中,诊断是一项复杂的任务。临床医生通常会对患者进行全面检查,而不仅仅是单个病变。当做出诊断时,他们还会考虑额外的信息,例如疾病的持续时间、患者是否处于高风险或低风险,以及患者的年龄等,这在本研究中没有提供。

尽管人工智能的表现令人印象深刻,但仍有改进的余地。对于来自未提供训练图像中的病变诊断,这些机器的准确性明显较低。

经验对于人类来说,是非常重要的。具有至少十年色素性皮肤病变诊断经验的参与医生表现最佳。

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    2020-04-07 howi
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    2020-04-19 minlingfeng
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    2019-07-13 anti-cancer

    谢谢梅斯分享这么多精彩信息

    0

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