AI can bridge different scientific modalities, enhancing our understanding of diseases like cancer by integrating imaging, genomics, and other data, and can help integrate sleep data with cardiovascular health and oncology to prevent cancer, which is challenging in traditional healthcare systems.

AI can reveal insights from tissue samples without the need for staining, preserving the sample for future tests.

AI can analyze various data sources, including lifestyle factors, to provide a more holistic view of health.

AI can analyze health records over time to predict future health outcomes, providing individuals with insights into their potential health trajectories.

AI can help create a new gold standard in medical diagnosis by providing consistent results where human experts may disagree.

AI can enhance efficiency in various steps of drug development, such as target identification, data analysis, and literature review, ultimately aiming to improve the overall success rate of drug discovery.

AI has the potential to improve diagnosis and treatment in healthcare, moving beyond just drug discovery.

AI can enhance our understanding of organ clocks, allowing us to assess the aging of vital organs and integrate this data with polygenic risk scores to better predict health outcomes.

AI can analyze medical images, but establishing a reliable ground truth for diagnoses can be challenging due to differing opinions among experts.