Healthcare research & technology advancements
Our team of clinicians, researchers, and engineers are all working together to create new AI and discover opportunities to increase the availability and accuracy of healthcare technologies globally, to realize long-term health technology potential.
Meet Med-PaLM 2, our large language model designed for the medical domain
Developing AI that can answer medical questions accurately has been a challenge for several decades. With Med-PaLM 2, a version of PaLM 2 fine-tuned for the medical domain, we showed state-of-the-art performance in answering medical licensing exam questions. With thorough human evaluation, we’re exploring how Med-PaLM 2 can help healthcare organizations by drafting responses, summarizing documents, and providing insights. Learn more.
Expanding the power of AI in medicine
We are building and testing AI models with the goal of helping alleviate the global shortages of physicians, as well as the low access to modern imaging and diagnostic tools in certain parts of the world. With improved tech, we hope to increase accessibility and help more patients receive timely and accurate diagnoses and care.
How DeepVariant is improving the accuracy of genomic analysis
Sequencing genomes enables us to identify variants in a person’s DNA that indicate genetic disorders such as an elevated risk for breast cancer. DeepVariant is an open-source variant caller that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
Healthcare research led by scientists, enhanced by Google
Google Health is providing secure technology to partners that helps doctors, nurses, and other healthcare professionals conduct research and help improve our understanding of health. If you are a researcher interested in working with Google Health to conduct health research, enter your details to be notified when Google Health is available for research partnerships.
Using AI to give doctors a 48-hour head start on life-threatening illness
In this research in Nature, we demonstrated how artificial intelligence could accurately predict acute kidney injuries (AKI) in patients up to 48 hours earlier than it is currently diagnosed. Notoriously difficult to spot, AKI affects up to one in five hospitalized patients in the US and UK, and deterioration can happen quickly. Read the article
Deep Learning
Protecting Patients
Deep Learning
Deep learning for electronic health records
In a paper published in npj Digital Medicine, we used deep learning models to make a broad set of predictions relevant to hospitalized patients using de-identified electronic health records, and showed how that model could be used to render an accurate prediction 24 hours after a patient was admitted to the hospital. Read the article
Protecting Patients
Protecting patients from medication errors
Research shows that 2% of hospitalized patients experience serious preventable medication-related incidents that can be life-threatening, cause permanent harm, or result in death. Published in Clinical Pharmacology and Therapeutics, our best-performing AI model was able to anticipate physician’s actual prescribing decisions 75% of the time, based on de-identified electronic health records and the doctor’s prescribing records. This is an early step towards testing the hypothesis that machine learning can support clinicians in ways that prevent mistakes and help to keep patients safe. Read the article
Discover the latest
Learn more about our most recent developments from Google’s health-related research and initiatives.
How AI Is advancing science and medicine
Google researchers have been exploring ways technologies could help advance the fields of medicine and science, working with scientists, doctors, and others in the field. In this video, we share a few research projects that have big potential.