Self-driven women's health equity through an innovative, inclusive, AI-driven and evidence-led decentralised precision medicine platform for awareness, diagnosis, and management of menopause.

更年期是女性生殖寿命的一次重大而不可避免的转变。英国更年期的平均年龄为51岁，而印度和其他发展中国家和低收入经济体的平均更年期年龄为46岁。全球有7亿女性正在经历这一转变。在英国，这一数字为1400万，而在印度，50岁以上的女性超过1亿。平均预期寿命和女性劳动力的增加将生育决定转移到了晚育年龄。更年期造成的心理和精神健康后果导致与健康有关的生活质量恶化，并导致生产性劳动力的经济损失。根据英国政府2017年发布的更年期经济影响报告，47%的英国劳动力--即所有女性工作者--将在工作期间经历更年期过渡。更年期经历是异质性的，需要个性化和背景知识来创建科学和证据导向的意识、诊断和管理。对于卵巢早衰、手术和药物引起的情况，对女性生殖系统功能的影响与自然更年期相同的情况知之甚少，自然更年期是与年龄相关的自然发育阶段。需要调查包括生活方式选择、长期健康状况和服药史在内的心理、生理和社会经济因素，以便为诊断和治疗做出准确的决定。缺乏临床专业知识，基础医学培训的空白，以及多年为准确诊断和建议而进行的专业临床实践，使这成为一个不可逾越的公共卫生挑战。荷尔蒙替代疗法正被作为最受欢迎的疗法提供，对可能最终增加医疗成本负担的长期后果知之甚少。此外，并不是每个女性都可以或更愿意接受激素替代。在某些程度上可能经历更年期转变的跨男性和非二元个体中，关于激素谱变化后果的科学证据有限。通过这个项目，我们将先进的计算科学(AI)、临床卓越和学术研究结合起来，通过允许患者和临床医生之间持续反馈循环的个性化医疗平台基础设施，创建更年期意识、诊断和管理的预测模型。它可以部署在一系列环境中，如全科诊所、社区健康中心、更年期诊所、远程健康诊所，从而分散医疗保健，并为妇女健康的自我驱动的健康公平提供可持续的商业和医疗模式，在消除健康不平等方面迈出一步。

Menopause is a significant and inevitable transition of a woman's reproductive life span. The average age of menopause in the UK is 51 in contrast to 46 in India and other countries with developing and low-income economies. There are 700 million women globally undergoing this transition. In the UK the number is 14 million while in India more than 100 million women are above the age of 50\. The increase in average life expectancy and female workforce has shifted reproductive decisions to later childbearing years. The psychological and mental health consequences from menopause leads to a deterioration of health-related quality of life and economic loss of the productive workforce. Per the economic impact of menopause published by the UK government in 2017, 47% of the UK workforce -- i.e., all female workers - will experience menopause transition during their working lives.Menopause experience is heterogenous requiring individualised and contextual knowledge for creating scientific and evidence-led awareness, diagnosis, and management. Little is known about Premature Ovarian Insufficiency, surgical, and medically induced situations that have the same effect on the functioning of a woman's reproductive system as natural menopause which is an age-related natural developmental stage. Psychological, physiological, as well as socio-economic factors including lifestyle choices, long-term health conditions and medication history need to be investigated to make accurate decisions for diagnosis and management. The lack of clinical expertise, gaps in fundamental medical training and years of specialised clinical practice for accurate diagnosis and recommendation makes this an insurmountable public health challenge.Hormonal replacement is being offered as the most popular therapy with little knowledge on long-term consequences that may ultimately increase the healthcare cost burdens. Moreover, not every woman can take or prefers to take hormone replacement. Limited scientific evidence exists on the hormone profile alteration consequences in transmasculine and non-binary individuals who may undergo menopause transition in some measure.Through this project we are uniting advanced computational science (AI), clinical excellence, and academic research to create prediction models for awareness, diagnosis, and management of menopause through a personalised healthcare platform infrastructure that allows for a continuous feedback loop between patients and clinicians. This can be deployed in a range of settings such as General Practice, Community health hubs, Menopause clinics, Telehealth clinics thereby decentralising healthcare and offering a sustainable business and healthcare model for self-driven health equity for women's health making a step-change in closing health inequalities.