Explainable AI recommendations for infectious disease management: providing clear, robust, and reliable communication to users

有效的决策对于控制传染病暴发至关重要。在英国，围绕感染预防和控制的糟糕决策每年给NHS造成约27亿英镑的损失。这主要是由于小组没有足够的时间和资源来正确分析疫情情况并确定采取的最有效行动。这些低效率导致住院时间延长、不必要的医疗程序和对患者的严重后果。感染预防和控制是一个复杂的领域，人工智能（AI）有可能通过支持最佳决策，彻底改变传染病的管理方式。然而，这些人工智能系统的黑箱特性和无法有效沟通阻碍了它们的大规模采用。因此，我们正在申请资金，将信任、透明度和沟通发展成为一种新的人工智能推荐工具，供感染预防和控制团队使用。通过提供这种程度的透明度和沟通，我们希望增加对人工智能工具的信任，并促进它们在感染预防和控制中的应用。该系统的潜在影响是深远的，不仅在医院感染预防和控制的主要市场，而且在提供算法推荐系统的透明度和沟通，使其能够在各种用例中被采用。随着该系统的开发，我们希望能够降低感染预防和控制决策失误带来的成本，并最终改善患者的预后。提高这一领域的决策效率有助于减少传染病的传播和预防未来的爆发。投资开发这类系统对于提供更好的护理和降低医疗成本至关重要。我们相信我们在NEX的研究。Q将导致开发一种有价值的工具，可以在各种医疗保健环境中采用，并最终改善患者的生活。

Effective decision-making is crucial to control outbreaks of infectious diseases. Poor decision-making around infection prevention and control costs the NHS an estimated £2.7 billion annually in the UK. This is primarily due to insufficient time and resources for teams to properly analyse outbreak situations and determine the most effective actions to take. These inefficiencies lead to prolonged lengths of stays, unnecessary medical procedures, and severe consequences for patients.Infection prevention and control is a complex field, and artificial intelligence (AI) has the potential to revolutionise how infectious diseases are managed by supporting optimal decision-making. However, the black-box nature of these AI systems and the inability to communicate effectively has hindered their adoption at scale. As a result, we are applying for funding to develop trust, transparency, and communication into a novel AI recommendation tool for infection prevention and control teams. By providing this level of transparency and communication, we hope to increase trust in AI tools and promote their adoption in infection prevention and control.The potential impacts of this system are far-reaching, not only in the primary marketplace of hospital infection prevention and control but also in providing transparency and communication of algorithm recommendation systems, enabling them to be adopted in various use cases. With the development of this system, we hope to decrease the costs associated with poor decision-making in infection prevention and control and ultimately improve patient outcomes. Improving the efficiency of decision-making in this field can help reduce the spread of infectious diseases and prevent future outbreaks.Investing in developing such systems is critical to provide better care and reducing healthcare costs. We believe that our research at NEX.Q will lead to the development of a valuable tool that can be adopted in various healthcare settings and ultimately improve patients' lives.