Written by:

Nick Passey

Head of Commercial Digital & IT, International & Japan, AstraZeneca

Pei-Chieh Fong

VP Medical, International, AstraZeneca

As new technologies and online capabilities continue to advance, 越来越明显的是,创新和数字工具将在未来的医疗保健中发挥重要作用. 当澳门葡京赌博游戏寻求解决大流行后世界中未满足的患者需求时,尤其如此, ensuring that our health systems are both resilient and future-proof.

At AstraZeneca, our ambition is to make health happen for people, society and the planet, 澳门葡京赌博游戏正在努力实现这一目标的方法之一是推动更多创新的发展, 以患者为中心的解决方案——在医疗保健领域利用创新工具的潜力.

Leading the way in early-stage detection with artificial intelligence (AI)

Through our A.Catalyst Network – an interconnected and dynamic, 全球共有20多个卫生创新中心,澳门葡京赌博游戏正在与不同的利益攸关方合作, including healthtech start-ups, local governments and cross-industry partners, 应对当前挑战,增加可负担和公平获得医疗保健的机会. The network embodies our commitment to advancing cutting-edge science, building a sustainable healthcare ecosystem and developing holistic, life-changing solutions for patients.

One such solution was created by our network partner, Qure.ai他开发了用于解释放射图像的深度学习算法. Their chest X-ray interpretation tool, ‘qXR', is able to automatically detect and localise up to 29 abnormalities, including those indicative of possible lung cancer.1,2 胸片有几个特征(如界限分明的结节或肿块), those with irregular margins, 以及那些病灶不明确的人),这可能表明肺癌的存在.1 ce标记的qXR算法不仅可以检测出具有这些特征的肺结节,而且准确率很高, but also mark out the position and size of these nodules.1,2

Globally, chest X-rays are the most commonly ordered diagnostic imaging test, with millions of scans performed every year.1, 3-5 虽然胸部x光很容易在初级保健和转诊环境中进行, the interpretation of these X-rays requires significant skill and experience, 缺乏阅读影像的专业知识会导致误诊或延误诊断.4,5,6 A study conducted by Qure.在使用人工智能解释胸部x光片时,其灵敏度提高了17%, compared to radiologist readings.1 这种早期发现的辅助手段可以为医疗专业人员治疗肺癌带来相当大的长期利益.7 It can also mean lower cost per-life-year saved.1

As part of a strategic collaboration across multiple hubs, the A.Catalyst Network will work with Qure.Ai将进一步探索应用深度学习算法来识别可疑的放射学肺部异常患者,并支持他们的转诊以获得明确的诊断. 该合作还将侧重于克服限制获得诊断工具以支持早期肺癌检测的障碍, and thereby reduce mortality rates and improve patient outcomes.

Our partnership with Qure.Ai的目标是利用并扩大这项技术的使用,以改善低收入和中等收入国家肺癌的早期检测. Activities such as these represent our wider, global commitment to patients with lung cancer, formalised through our partnership with the Lung Ambition Alliance, 哪个是为了消除肺癌作为死亡原因而建立的. In this, 澳门葡京赌博游戏将继续努力开发变革性的新可能性, so that we may better support the patient’s journey through diagnosis, treatment and disease management.

Improving vaccine confidence through digital engagement

As scientific leaders in our respective markets, 澳门葡京赌博游戏相信澳门葡京赌博游戏有责任照顾病人和生活在澳门葡京赌博游戏社区的人们, not only in terms of diagnosis and treatment, but also with regard to disease awareness and education. 让病人更积极地参与自己的健康, 澳门葡京赌博游戏的目标是创建一个更可持续的医疗模式,既把他们放在中心位置,使他们能够做出明智的决定,帮助确保他们的健康.

澳门葡京赌博游戏的360º疫苗信心建设计划建立了一个整体框架,主要是在一些重点国家的医学界和普通民众中增进对COVID-19的理解和认识, developing nations in Latin America and East Asia. 澳门葡京赌博游戏利用澳门葡京赌博游戏的数字能力并提供量身定制的内容,为在迫切需要的时候更好地了解COVID-19奠定了基础.

Rolled out in phases, the initiative was structured around three strategic pillars: a social-media-based strategy that sought to identify and gather insights that would shape our next steps; a medical education programme aimed at key external experts and healthcare professionals (HCPs) that would allow them to better educate others about COVID-19; and a digital awareness campaign that would promote greater awareness and understanding by utilising a range of bespoke, educational resources to support communication and engagement. To date, 已确定并与150多名数字外部专家进行了接触, addressing concerns that they may have.

Delivering the healthcare of tomorrow

Both our partnership with Qure.ai和360º疫苗信心建设运动最近在2022年路透社制药奖上获得认可, 他们代表了澳门葡京赌博游戏在医疗保健领域掀起革命的持久雄心, putting patients at the centre of our focus.

As leaders in the pharmaceutical industry, we understand that it is our responsibility to establish a robust, sustainable healthcare ecosystem that serves people, society and the planet, both now and into the future. Taking bold action through initiatives and partnerships such as these, we are reimaging and reshaping approaches to healthcare, 确保患者的体验和结果得到考虑,并且确实被视为整个生态系统的优先事项.

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1. Mahboub B, Shuri H, Al Bastaki U, et al. 将人工智能系统与放射科医生在胸部x光片上识别结节进行比较. 2020. Submitted manuscript.

2. Qure,ai. Automated Chest X-ray Interpretation – qXR. 2020. Available at:

http://www.qure.ai/qxr.html. Accessed 19th November 2020.

3. World Health Organization. Ionizing radiation. Chapter 1: Scientific background. 2016. Available at: http://www.who.int/ionizing_radiation/pub_meet/chapter1.pdf?ua=1. Accessed 19th November 2020.

4. Raoof S, Feigin D, Sung A, et al. Interpretation of plain chest roentgenogram. Chest. 2012;141(2):545-58.

5. Coche EE, Ghaye B, de May J, Duyck P (eds.). Comparative Interpretation of CT and Standard Radiography of the Chest. 2011. Springer-Verlag Berlin Heidelberg.

6. RSNA. Radiologist Shortage in the U.K. Continues to Deepen. 24th May 2019. Available at: http://www.rsna.org/en/news/2019/May/uk-radiology-shortage. Accessed 19th November 2020.

7. Gossner J. Lung cancer screening-don't forget the chest radiograph. World J Radiol. 2014;6(4):116-8.

Veeva ID: Z2-3580
Date of preparation: December 2022


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