Generative models improve fairness of medical classifiers under distribution shifts | Nature Medicine
Domain generalization is a ubiquitous challenge for machine learning in healthcare. Model performance in real-world conditions might be lower than expected because of discrepancies between the data encountered during deployment and development. Underrepresentation of some groups or conditions during model development is a common cause of this phenomenon. This challenge is often not readily addressed by targeted data acquisition and ‘labeling’ by expert clinicians, which can be prohibitively expensive or practically impossible because of the rarity of conditions or the available clinical expertise. Researchers hypothesize that advances in generative artificial intelligence can help mitigate this unmet need in a steerable fashion, enriching the training dataset with synthetic examples that address shortfalls of underrepresented conditions or subgroups. They show that diffusion models can automatically learn realistic augmentations from data in a label-efficient manner.
Single Cell Atlas: a single-cell multi-omics human cell encyclopedia | Genome Biology
Single-cell sequencing datasets are key in biology and medicine for unraveling insights into heterogeneous cell populations with unprecedented resolution. Here, researchers construct a single-cell multi-omics map of human tissues through in-depth characterizations of datasets from five single-cell omics, spatial transcriptomics, and two bulk omics across 125 healthy adult and fetal tissues. They construct its complement web-based platform, the Single Cell Atlas (SCA, www.singlecellatlas.org), to enable vast interactive data exploration of deep multi-omics signatures across human fetal and adult tissues.
brainlife.io: a decentralized and open-source cloud platform to support neuroscience research | Nature Methods
Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects.