We’re making progress in using AI to improve disease detection and diagnosis, and to better understand health conditions:

• Deepening scientific discovery: Our Nobel-Prize winning AlphaFold has predicted all 200 million protein structures known to science, providing a new basis for understanding and researching diseases. It is now used by 4 million researchers in 190 countries in areas from drug discovery to understanding neglected diseases like Chagas disease and leishmaniasis. AlphaMissense is helping researchers predict disease-causing genetic mutations. And now, we’re building on AlphaFold and AlphaMissense with AlphaGenome Atlas, offering scientists predictive insights into how genetic variations alter cellular behavior.
• Earlier detection: Our recent breast cancer study with Imperial College London and the U.K.’s NHS showed AI can detect 25% of interval cancers previously missed in mammograms of 175,000 women. At the same time, we’re making meaningful progress in tools to help detect lung cancer, colorectal cancer, and genetic mutations in tumor cells.
• Global screenings: For tuberculosis — where ~40% of infected people worldwide go undiagnosed — our chest X-ray (used by Nexus Intelligence) has screened over 25,000 x-rays across 40 locations in six nations. We are also using bioacoustic models to detect TB via coughs using Health Acoustic Representations. Meanwhile, our diabetic retinopathy model, developed with partners, has supported more than 1.15 million screenings globally, with plans to expand to 6 million over the next decade to help detect a treatable but growing cause of preventable blindness.
• Expanding access: We’re pioneering the use of everyday smart phones and wearables for early detection of cardiovascular disease, insulin resistance, hypertension, loss of pulse, and passive heart rate monitoring. We’re working with leaders in Arkansas to help develop a blueprint for improving health outcomes in rural areas.
• Tools for scientists and health practitioners: Collaborative AI tools like Co-Scientist are helping researchers accelerate and expand core steps of the scientific method, like generating and validating novel hypotheses (such as identifying new therapeutic applications for existing drugs for acute myeloid leukemia). We have also open-sourced AI tools like DeepConsensus, DeepVariant, and DeepPolisher. Over the last decade, these tools have assisted in completing the human genome, drafting the first pangenome, and enabling ongoing work as part of the Human Pangenome Reference Consortium, better representing human genetic diversity and allowing experts to more accurately diagnose and treat diseases. Through AMIE (Articulate Medical Intelligence Explorer), we are continuing to work on prospective evidence in real-world settings, collaborating with academic and medical institutions (e.g., Beth Israel Deaconess Center), and conducting a first-of-its-kind nationwide trial in real-world care settings. AMIE assists those providing care on the frontlines — freeing up doctors to spend more time with their patients.