Abstract The impact of data quality and quantity (on modeling) is always critical, no matter in traditional statistics or machine learning (deep learning). Data privacy is always the top consideration for digital health and health informatics. However, it becomes a significant obstacle when it comes
Abstract Data science holds the potential to increase the efficiency and effectiveness of intensive care units, as well as improving patient outcomes. A lot of research in this space focuses on predictive algorithms: solutions to support the early identification of shock, sepsis, hypotension, and ot
Abstract Data science holds the potential to increase the efficiency and effectiveness of surgical workflow, as well as improving patient outcomes in the operating room. Artificial intelligence is already informing risk prediction and decision support, increasingly drawing on live data from electron
Abstract “If we are not careful, AI will perpetuate the bias in this world. Computers learn how to be racist, sexist, and prejudiced in a similar way that a child does. The computers learn from their creator - us.” Aylin Caliskan, computer scientist The COVID-19 pandemic and the protests for
Abstract The global health crisis has seen exponential acceleration in the deployment of telemedicine, with health leaders expecting at least 30% of clinics to remain virtual permanently. For healthcare administrators, this presents both challenges and opportunities, including: The need to rethink p
When? Friday 31st July: 7am - 2pm (PDT) Saturday 1st August: 8am - 11am (PDT) Abstract Medicine has been a clinical science, supported by data. Medicine is about to become a data science, supported by clinicians. Artificial intelligence is rapidly becoming more pervasive in medicine
Abstract Data science holds the potential to increase the efficiency and effectiveness of cardiology workflow, as well as improving patient outcomes. Artificial intelligence is already being used to predict those at risk of heart disease at a population level, as well as other risk prediction modell
Abstract Data science holds the potential to increase the efficiency and effectiveness of radiology workflow, as well as improving patient outcomes. Artificial intelligence is already being used to triage cases and prioritise workflow, increasing efficiency in radiology practice and decreasing burno
Abstract Data science holds the potential to increase the efficiency and effectiveness of healthcare delivery, improving patient outcomes and reducing costs. Artificial intelligence is already being used extensively in image analysis, risk prediction, workflow prioritisation, to triage cases and pri
Abstract The potential of data science to increase the efficiency and effectiveness of critical care units, as well as improving patient outcomes, is well established. And yet, examples of successful deployment of AI solutions in this setting are still relatively few and far between. What are the ma
