小柯机器人

GestaltMatcher利用面部表型描述来促进罕见疾病的匹配
2022-02-13 21:40

德国伯恩大学Peter M. Krawitz团队发现,GestaltMatcher可利用面部表型描述来促进罕见疾病的匹配。2022年2月10日,国际知名学术期刊《自然—遗传学》在线发表了这一成果。

为了提高对超罕见疾病的识别,研究人员开发了GestaltMatcher,一个基于深度卷积神经网络的肖像编码器。17,560名患有1,115种罕见疾病的患者的照片被用来定义一个临床脸部表型空间,在这个空间中,病例之间的距离定义了综合症的相似性。结果表明,即使该疾病没有被纳入训练集,患者也能与具有相同分子诊断的其他人相匹配。与突变数据一起,GestaltMatcher不仅可以加速对超罕见疾病和面部畸形患者的临床诊断,而且还能划定新的表型。

据介绍,许多单基因疾病会导致特征性的面部形态。人工智能可以支持医生识别这些模式,通过对数以千计的病人照片进行训练,将面部表型与潜在的综合症联系起来。然而,这种"监督"方法意味着只有当该疾病是训练集的一部分时才有可能进行诊断。

附:英文原文

Title: GestaltMatcher facilitates rare disease matching using facial phenotype descriptors

Author: Hsieh, Tzung-Chien, Bar-Haim, Aviram, Moosa, Shahida, Ehmke, Nadja, Gripp, Karen W., Pantel, Jean Tori, Danyel, Magdalena, Mensah, Martin Atta, Horn, Denise, Rosnev, Stanislav, Fleischer, Nicole, Bonini, Guilherme, Hustinx, Alexander, Schmid, Alexander, Knaus, Alexej, Javanmardi, Behnam, Klinkhammer, Hannah, Lesmann, Hellen, Sivalingam, Sugirthan, Kamphans, Tom, Meiswinkel, Wolfgang, Ebstein, Frdric, Krger, Elke, Kry, Sbastien, Bzieau, Stphane, Schmidt, Axel, Peters, Sophia, Engels, Hartmut, Mangold, Elisabeth, Krei, Martina, Cremer, Kirsten, Perne, Claudia, Betz, Regina C., Bender, Tim, Grundmann-Hauser, Kathrin, Haack, Tobias B., Wagner, Matias, Brunet, Theresa, Bentzen, Heidi Beate, Averdunk, Luisa, Coetzer, Kimberly Christine, Lyon, Gholson J., Spielmann, Malte, Schaaf, Christian P., Mundlos, Stefan, Nthen, Markus M., Krawitz, Peter M.

Issue&Volume: 2022-02-10

Abstract: Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.

DOI: 10.1038/s41588-021-01010-x

Source: https://www.nature.com/articles/s41588-021-01010-x

 

Nature Genetics:《自然—遗传学》,创刊于1992年。隶属于施普林格·自然出版集团,最新IF:41.307
官方网址:https://www.nature.com/ng/
投稿链接:https://mts-ng.nature.com/cgi-bin/main.plex


本期文章:《自然—遗传学》:Online/在线发表

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