AI-driven laryngeal cancer assessment

我们的愿景是利用机器学习从患者的智能手机录音中检测喉癌风险。目的是自信地将良性声带问题转移到更合适的护理途径。今天，在初级保健中出现“声音嘶哑”的患者被转介到头颈癌诊所。在英国每年约28000例转诊患者中，绝大多数（93%）并没有癌症。如果我们能够提供一种人工智能驱动的智能手机测试来简化这一过程，那么对患者和医疗保健系统将有多重好处。来自利物浦大学医院NHS基金会信托的头颈癌外科医生和耳鼻喉科顾问是该项目背后的推动力。他们认为，听病人嘶哑的声音就能提供足够的信息来排除癌症。在这个项目中，我们将通过智能手机使用机器学习来倾听声音，并开发一个原型系统，将患者送到正确的护理地点。最终，这样的系统可以部署在初级保健，在每一个全科医生，导致显著的病人利益和NHS的成本节约。

Our vision is to use machine learning to detect laryngeal cancer risk from smartphone voice recordings of patients. The purpose is to confidently divert benign vocal problems into more appropriate care pathways.Today, patients presenting at primary care with a "hoarse voice" are referred to a head and neck cancer clinic. Of the estimated 28,000 annual referrals in England, the vast majority (93%) do not have cancer. If we are able to provide an AI-driven smartphone test to streamline this process, there are multiple benefits to patients and the healthcare system. Head and neck cancer surgeons and ENT consultants from the Liverpool University Hospitals NHS Foundation Trust are the driving force behind this project. They believe that listening to a patient's hoarse voice provides sufficient information to rule out cancer. In this project, we will use machine learning to listen to a voice, via a smartphone, and develop a prototype system to route patients to the right care. Eventually such a system could be deployed in primary care, at every GP, resulting in significant patient benefit and cost savings to the NHS.