Digital Transformation in Healthcare - Healthcare is undergoing digital transformation with paperless hospitals and automated processes like blood analysis [2] - Accumulated data facilitates predictive analytics, forecasting patient needs weeks or months in advance [4] Future Medical Systems Requirements - Future medical systems need to be adaptive, sustainable, and equitable, integrating technology for everyone's benefit [5][6] - Systems should anticipate individual patient demands upon arrival, personalizing treatment and tests [9] - Addressing patient flow peaks, such as during respiratory virus seasons, is crucial [7] The Role of Algorithms - Algorithms are already improving diagnostics through image enhancement in ultrasounds and CT scans [4] - Algorithms alone cannot design future-ready medical systems; empathy is essential [8][20] - Hybrid models using AI chatbots for preliminary assessments can prepare clinicians and augment empathy [18][19] Ethical Considerations - Respect for patient autonomy is necessary, allowing individuals to opt out of data collection and analysis [12] - Balancing efficiency with human experience is critical, as current systems prioritize efficiency [16] - Empathy should be a measurable design metric, tested for its ability to detect and respond to patient feelings [22] Co-creation and the Future - Co-creation with clinicians, patients, researchers, and engineers is vital for capturing diverse perspectives [23] - The goal is to use data to restore the human touch in medicine, enabling algorithms to design future-ready systems [23]