Frida Hauler has a Ph.D. in medical physics, specializing in multi-modal image registration techniques ready for clinical use in radiotherapy.
Frida Hauler has a Ph.D. in medical physics, specializing in multi-modal image registration techniques ready for clinical use in radiotherapy. She worked as a portfolio manager and project engineer for Brainlab, and recently migrated towards AI-based therapy guidance to cure atrial fibrillation, working at Ablacon Inc. With years of multidisciplinary experience in computer science and biomedical engineering, she is a real expert in her field. We had an inspiring conversation in our IseeQ office a while ago, discussing the current trends of the market, radiotherapy, the importance of human factors against technology, and her vision of the future. The following article is written by us, based on Frida’s words.
The medical industry is dominated by a few key players, like Siemens Healthineers, Elekta, GE, Philips, and Boston Scientific, but innovation is often driven by start-ups and smaller research labs. On the other hand, research and medical-device development both require huge capital and resources, which are more available for larger firms. Rigid bureaucratic systems with confusing policies are also making it harder to introduce a new product. Especially one that conveys cutting-edge technology into an already existing tool, it is not uncommon that the development process stretches up to 3-5 years. Verification and validation steps, a clinical evaluation plan, and clinical trials all have to precede the adaption to diagnostics or treatments.
Furthermore, the standardized nature of the market mostly allows new technologies like machine learning to be added to or integrated into an already used device. This standardization creates a segmented workflow of multiple steps, which can be frustrating to work within.
Finding ideal solutions to real-life problems can be a struggle. Sometimes technological novelties only include some key steps from a difficult line of actions, so human attention and intervention are still very much required. This is one of the reasons why we don’t have self-operating hospitals and robot doctors yet.
In radiotherapy for example accurate contouring of a tumor is critical to define a treatment plan. The aim is to kill the tumor but spare the surrounding organs and healthy tissue at risk. In clinical practice, accurate, expert-based contouring is time-consuming while automated tools are inaccurate, and they need manual correction. For doctors, validation and verification can be boring, while research-like prototyping is believed to be more exciting. The pressure of relying on and taking the responsibility for decisions that a machine makes might also be overwhelming- This is why revolutionary knowledge gets “lost” in Ph.D. essays and researches.
However, there is still a need for automated pattern recognition and data-driven solutions in healthcare. Frida believes in a future where physicians are freed from the tedious, time-consuming tasks by automated, high-quality systems with quantified uncertainties. A hospital that functions as smoothly as a factory line, in which physicians can focus on spending quality time with their patients … in 20 years it might be common.
Cybersecurity, data verification, and patient approval of data handling are determinant factors when it comes to new technologies. Just until recently, hospitals prevented online security issues by not providing internet access. Data collection from patients was a strictly controlled process, including clinical trials and an approval by an ethical board.
Today, AI-based medical devices are not only able to store, but to generate a vast amount of data by themselves, giving them the potential to transform the whole healthcare industry. There are many players who could benefit from a possible mistake, even legal entities like insurance companies, so ensuring safety while handling is of utmost importance. Managing boards and authorities now have to be able to adjust to new standards, and navigate confidently not only in their fields of expertise but also while dealing with new technology and cybersecurity measures. Documentation can now be delegated to software, and device developing teams will not be overwhelmed by them anymore. Time and resources to properly evaluate and validate the safety of a medical product should not be drawn away from knowledgeable experts. With the correct legislation, everyone could be satisfied.
Despite its challenges, the market is still thriving. Leading players are on the way to realize that the standards are changing, and they need to step up their game and catch up with emerging technological advancements to remain in their positions. Leaders with a closed mindset will soon realize that the times have changed and that they need to challenge their own status quo. Coming up with more resilient and user-friendly services will provide an advantage for anyone brave enough to seize it. Experts will navigate through the current difficulties to make high-tech products sellable and part of the clinical routine, in a safe, standardized, legally regulated framework.
Frida and IseeQ both see the future bright: with newly adopted policies our data will be stored safely, only used to improve on our diagnoses and treatments. AI will not only help with early and efficient recognition of illnesses but with prevention too. Providing accurate medical advice to the patients can also become a job of virtual assistants or chatbots, and with risk scoring calculations and predictive analyses, the pressure of decision making can also be lifted from doctors’ shoulders.
Though we can only hope that the future will prove us right, we immensely enjoyed listening to Frida share her experience and expectations. We can’t wait to see an innovative, revolutionized and more efficient industry emerge.
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