Communications Medicine
A selective open access journal from Nature Portfolio publishing high-quality research, reviews and commentary across all clinical, translational, and public health research fields.
Unlocking the Power of Deep Learning for Multi-Omic Molecular Profiling: Insights from a Pan-Cancer Study
We investigated the capability of deep learning (DL) for molecular profiling using routine pathology images. Distilling results from over 4,000 biomarkers, we found that DL can establish status of many biomarkers across multiple cancers, indicating its potential for revolutionising patient care.
How machine learning helped us uncover key environmental and clinical risk factors to child health
The environment in which a child grows up affects its development and well-being later in life. These effects do not happen in isolation – whether due to air pollution, exposure to cleaning products, or a family's social capital, they all simultaneously impact a child's health.
Outdoor air pollution changes maturation patterns of the brain's white matter in sex-specific ways
Outdoor air pollution, a ubiquitous neurotoxicant, is shown to change white matter maturation patterns in differential ways depending on biological sex in a large sample of US-based youths, in the first longitudinal study of its kind.
How large language models can help scale citizen science in chronic disease research
We have observed a consistent desire among persons with chronic diseases to tell their story and be heard. Engaging them more in health research may demand new ways for capturing and analyzing such free-text narratives. Large language models can streamline the analysis and lead to novel insights.
Using CRFasRNNs in Brain Extraction
We study a unique way of using CRFs in brain extraction. To our knowledge, this is the first time successfully using CRFs within the Deep Learning network for 3D medical image segmentation.
