Case Studies

Publications

Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats
We illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19.
A predictive atlas of disease onset from retinal fundus photographs
We have unlock the predictive potential of retinal images for genetic discovery and disease risk assessment across more than 750 conditions. Our approach not only outperforms traditional methods in predicting diseases but also uncovers new genetic associations. We believe this fusion of AI and genetics will transform target identification and prioritization.
A scalable, secure, and interoperable platform for deep data-driven health management
The surge in biomedical data from wearable sensors, electronic health records, and genomics is revolutionizing healthcare, offering significant health improvement opportunities while posing challenges in data management and analysis. To meet these challenges, we developed a tool utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics.
Large-scale exome sequence analysis identifies sex- and age-specific determinants of obesity
Obesity contributes substantially to the global burden of disease. We studied how genetics influence obesity using UK Biobank data and found certain rare gene variations impact obesity differently in men, women, and children showing how these variations affect processes like cell death and DNA damage.
Understanding the genetic complexity of puberty timing across the allele frequency spectrum
The timing of puberty affects future health outcomes. We investigated the underlying biological mechanisms, performing multi-ancestry genetic analyses in ∼800,000 women, identifying 1,080 independent signals associated with puberty timing.
Medical history predicts phenome-wide disease onset (in press)
Current medicine lacks data-driven guidance, underutilizing the predictive value of medical histories for diseases. We explored the potential of the medical history to inform on the phenome-wide risk of onset for 1,883 disease endpoints across clinical specialties.
Metabolomic Data Predicts Common Disease Onset
Risk stratification is critical for the identification of high-risk individuals. Here we show the potential of NMR metabolomic profiles to predict multidisease onset across 24 common conditions, including metabolic, vascular, respiratory, musculoskeletal and neurological diseases and cancers.

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