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Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine. © 2021, The Author(s).

An evidence-based reassessment of the phylogenetic relationships of conodonts shows that they are not “stem” gnathostomes, nor vertebrates, and not even craniates. A significant group of conodont workers have proposed or accepted a craniate designation for the conodont animal, an interpretation that is increasingly becoming established as accepted “fact”. Against this prevailing trend, our conclusion is based on a revised analysis of traditional morphological features of both discrete conodont elements and apparatuses, histological investigation and a revised cladistic analysis modifying that used in the keystone publication promoted as proof of the hypothesis that conodonts are vertebrates. Our study suggests that conodonts possibly were not even chordates but demonstration of this is beyond the scope of this paper. To summarize, in conodonts there is low cephalization; presence of simple V-shaped trunk musculature and unique large-crystal albid material in the elements; lack of a dermal skeleton including characteristic vertebrate hard tissues of bone, dentine and enamel; lack of odontodes with bone of attachment and a unique pulp system; lack of segmentally-arranged paraxial elements and dermal elements in median fins, all of which supports neither a vertebrate nor a craniate relationship for conodonts.

No abstract is available for this article. doi:10.1002/mmng.20040070102