Developing Reinforcement Learning and Artificial Intelligence Tools to Support Clinical Care Including Care for Women with Perimenopausal and Menopaus
Developing Reinforcement Learning and Artificial Intelligence Tools to Support Clinical Care Including Care for Women with Perimenopausal and Menopaus
批准号:
2889702
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
这个项目是由利物浦大学与纽森健康公司合作开发的。更年期是女性生活中的一件大事,它会对生活质量产生负面影响,并增加对健康的担忧。尽管更年期本身不会导致癌症,但更年期的过渡期可能与复杂的疾病有关,包括乳腺癌和子宫内膜癌。激素替代疗法(HRT)的优点和缺点也是一个争论的主题。该项目旨在通过利用机器学习和深度学习中的先进技术,为出现围绝经期和更年期症状的女性带来革命性的临床护理。我们的目标是开发机器学习方法,以更好地解释和理解Newson Health的内部临床数据,这些数据可以提供有临床价值的见解,并具有改善患者护理的潜力。我们还致力于开发深度强化学习方法,以便从临床数据中自动学习最优的个性化治疗方案。我们将探索有监督/无监督和强化学习的组合,以利用之前收集的临床数据来帮助在线学习过程。离线强化学习和生成式人工智能工具也可能在我们的开发过程中发挥重要作用。我们的研究有可能改善治疗结果和个性化护理。
英文摘要
This project is being developed by the University of Liverpool in partnership with Newson Health. Menopause is a significant event in a woman's life, which can negatively affect the quality of life and increase health concerns. Although menopause itself doesn't cause cancer, the transitional phase to menopause can present relations to complex diseases, including breast cancer and endometrial cancer. The advantages and drawbacks of Hormone Replacement Therapy (HRT) are also a subject of debate. This project aims to revolutionise clinical care for women experiencing perimenopausal and menopausal symptoms by leveraging advanced techniques in Machine Learning and Deep Learning.We aim to develop machine learning methods to better interpret and understand Newson Health's internal clinical data, which can provide clinically valuable insights and has the potential to improve patient care. We also aim to develop deep reinforcement learning methods to automatically learn optimal individualised treatment regimens from clinical data. We will explore the combination of supervised/unsupervised and reinforcement learning to leverage previously collected clinical data to aid the online learning process. Offline reinforcement learning and Generative AI tools will also likely play an important role in our development process. Our research has the potential to improve treatment outcomes and personalised care.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
海桑属杂种区强化(Reinforcement)的检验与遗传基础研究
-
批准号:30800060
-
项目类别:青年科学基金项目
-
资助金额:23.0万元
-
批准年份:2008
-
负责人:周仁超
-
依托单位: