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As Nature Medicine celebrates its 25th anniversary, we bring you a special Focus on Digital Medicine that highlights the new technologies transforming medicine and healthcare, as well as the related regulatory challenges ahead.
AI is used increasingly in medical diagnostics. Here, the authors present a deep learning model that masters medical knowledge, demonstrated by it having passed the written test of the 2017 National Medical Licensing Examination in China, and can provide help with clinical diagnosis based on electronic health care records.
Selection of the right cancer treatment is still a challenge. Here, the authors introduce a framework to analyze treatment benefits, using the idea that patients with similar genetic tumor profiles receiving different treatments can be used to model their responses to the alternative treatment.
Anemia has a global prevalence of over 2 billion people and is diagnosed via blood-based laboratory test. Here the authors describe a smartphone app that can estimate hemoglobin levels and detect anemia by analyzing pictures of fingernail beds taken with a smartphone and without the need of any external equipment.
In this Review, Yacoub and McLeod summarize the rationale for monitoring patients with heart failure or pulmonary arterial hypertension to detect haemodynamic changes that predict the deterioration from subclinical to overt disease, the transition from noninvasive to implantable devices and the current and anticipated clinical use of these devices.
Computational models are increasingly used in cardiology to integrate multiple data sets from individual patients and create virtual-patient simulations. In this Review, Niederer and colleagues discuss how multi-scale models of cardiac electrophysiology and mechanics can support diagnostic assessment and clinical decision-making and pave the way to personalized cardiac care.
Mental health technologies, such as apps, clinical texting, social media platforms and web-based tools, have arrived. Channelling these resources to help people with serious mental illnesses, clinicians in need of support, and people in low-and middle-income countries will have the most impact on the global burden of mental illness.
Clinical trials for Alzheimer disease drugs have an exceptionally high failure rate, discouraging investment in the field despite the unmet medical need. Drug developers need to more effectively harness existing and emerging data and digital technologies to improve the likelihood of success.
Information Exchange and Data Transformation (INFORMED), a multidisciplinary initiative anchored in the FDA Oncology Center of Excellence, is a decentralized science and technology incubator designed to harness the power of big data and advanced analytics to improve disease outcomes.
Analysis of genetic data and blood lipid measurements from over 300,000 participants in the Million Veteran Program identifies new associations for blood lipid traits.
Genome-wide association analysis using electronic health record data from >94,000 individuals identifies loci associated with plasma lipid concentrations. Longitudinal measurements allow for the calculation of genetic risk scores and increase the variance explained.