Companions, AI, and quantum computers at the service of overworked doctors

Every 1.8 seconds, someone somewhere in the world is diagnosed with cancer. The news brings a heavy burden. It’s the beginning of a period of uncertainty full of questions and hopes. The disease takes many forms, and the diagnosis must be specific: What cancer, what stage, and what are the molecular and genetic characteristics? What treatment is most appropriate? Once treatment is in progress, the physicians need to regularly make complex decisions so they can recommend the best next step in the patient’s personal treatment path.

There are high implications for each of the decisions the physicians make: What medication is needed, and at what dose? What lab analyses are indicated, what genetic tests, what type of imaging, and what form of chemotherapy or radiotherapy? Do the latest studies offer new suggestions? And at the same time, the conditions for structuring a sequence of actions are anything but favorable: Many physicians are chronically overworked and have to make decisions under extreme pressure at the end of what are often long and exhausting shifts. The world will be short 15 million healthcare workers by 2030, and 80 percent of MDs are at high risk for burnout driven by exhaustion. The world’s population continues to grow, and half of humanity now has no access to high-quality healthcare.

Technology is helping resolve this dilemma.

Digitalization is the key, artificial intelligence (AI) and quantum computers (QCs) are two of its key components, and therefore they’re all important elements in our response to the question of how we can best support medical professionals. For example, AI helps radiologists precisely identify suspicious structures on images even after lengthy shifts, which can help diagnose conditions like COVID-19. Organs can be automatically identified and contoured on images, and 3D datasets help plan the ideal course of radiotherapy. Algorithms can draw the physician’s attention to the latest studies and guidelines.

In principle, physicians could read all these materials themselves, but in the field of internal medicine alone they’d have to read 17 articles a day, 365 days a year.

AI has started to support more accurate and personalized decision-making to achieve the best possible treatment outcomes. I see it as an untiring digital companion that’s there to support physicians with details and information they’re unable to gather themselves because there simply isn’t enough time. It’s all about aggregating, correlating, and displaying the relevant patient-specific information at all stages throughout the clinical process. The final decision always rests with the physician.

AI is the key to more accurate diagnoses, better therapies, and improved access to accurate knowledge for the physician. Without high-quality medical data, there’s no intelligence in AI. That's the prerequisite for successfully training algorithms and unlocking their full potential for medicine. Access to data is by no means a question of technology alone; rather, it’s about trust. Health data doesn’t belong to industry or to the government, it belongs to the patients and only to them. Patients' consent to the use of their data is essential to making progress in the digital transformation of our healthcare systems. It’s important that we work together to understand and embrace the value of this technology so that we can employ it for the benefit of our communities. More than ever, guidelines for accessing, processing, and storing health data are imperative, in conjunction with a consistent and uncompromising application of data protection rules.

Another element in shaping the future of the digital healthcare system is currently taking shape in a number of advanced physics labs: quantum computers (QCs). QCs are still in an intermediate development stage but are progressing fast: While they’re far from ready for commercial use, they’ve grown well beyond the realm of science fiction. This was demonstrated recently at a meeting of experts at IEEE, the world’s largest and most influential organization that’s working on technical standards for QCs. If you’d like a deep dive into the topic, watch this session where I shared my perspective on the impact of AI and QC for healthcare:

It’s still impossible to forecast just what QC’s potential will be for evaluating medical images, image reconstruction, diagnoses, and treatments, but the initial studies give me plenty of good reasons to not underestimate their promise. For example, quantum calculations could perform large-scale comparisons between molecules to identify new active agents for cancer therapy much more quickly than is currently possible. I expect them to be able to discover new connections in the vast quantities of data gathered from wearables and other sensors to improve clinical decision-making processes. Their special capabilities may lead to in-silico trials with no human subjects. We may also see advances in the speed of evaluating sequences of genetic material consisting of billions of components.

At the same time, I’m aware of another unique feature of QCs: They can decipher many of the encryption techniques we’re familiar with, which means we’ll need new security measures – in particular, to protect patient data and prevent cyberattacks. Security by Design is our response, and it will need to evolve and be enhanced alongside the new developments in QC. To ensure effective data security, we’ll have to adopt new approaches that go beyond securing individual devices or processes. Other opportunities provided by QC could help us develop dynamic and accelerated security that will protect data in almost the same way as the human immune system. Protection – everywhere and all the time.

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This approach to technology will create trust in medicine, technology, and our increasingly digitalized healthcare system. Our teams at Siemens Healthineers are driven by one purpose: to drive innovation that helps humans live longer and healthier. That’s an important contribution to society, because it means we can tackle the challenges of our healthcare system AND achieve improved quality and better healthcare – safer and faster.