The Role of AI in Transforming Healthcare in CEE

Discover how Artificial Intelligence is reshaping healthcare in Central and Eastern Europe, promising unprecedented advancements and posing new ethical dilemmas. Today, we stand at a crossroads reminiscent of the 1980s when computers first entered the medical field—met with scepticism yet heralding a technological revolution. As history debates between the sceptics' caution and the pioneers' zeal for progress, AI now challenges us to envision a future where it becomes as fundamental to healthcare as computers have. Will we navigate its ethical mazes to unlock a new era of precision and personalization, or will caution temper its integration?

Revolution or Challenge?

In the heart of Europe, a revolution is underway. Artificial Intelligence (AI) is not just changing industries; it's redefining healthcare in Central and Eastern Europe (CEE). The region, known for its rich history and diverse cultures, is now becoming a hotspot for AI-driven medical innovations. This transformation is not only about technology but also about the visionaries behind it — professionals and teams dedicated to merging AI with healthcare to address some of the sector's most pressing challenges.

In the realm of healthcare, AI is not just a tool but a transformative force that redefines the boundaries of medical treatment and patient care. As we harness the power of Artificial General Intelligence and generative AI, we're not merely automating tasks; we're opening doors to unprecedented precision in diagnostics and personalized therapies.

Yet, with great power comes great responsibility.

We must navigate this new frontier with a keen eye on ethics, ensuring that every advancement brings us closer to a healthcare system that's not only more efficient but also more equitable and human-centric.

The Vanguard of AI in Diagnostics and Personalized Care

One of the most compelling illustrations of AI's impact is found in the collaboration between ?wi?tokrzyskie Centrum Onkologii and AGH University of Krakow. Together, they are pioneering personalized radiotherapy treatments, leveraging AI to tailor therapies to the unique genetic makeup of each patient's cancer[1]. This partnership exemplifies how interdisciplinary collaboration can lead to breakthroughs that once seemed beyond reach.

Similarly, in Katowice, scientists at a leading clinic have developed an AI algorithm that revolutionizes infertility treatment. Their algorithm assesses embryos with unparalleled precision, offering hope to countless couples struggling to conceive[2].

"The algorithm can analyze thousands of images within a few minutes. A human will never be able to achieve this. The data provided by artificial intelligence is incredibly valuable – it can provide information about the health and quality of the embryo, which can affect the chances of success of the in vitro fertilization procedure." — explains Dr. Wojciech Grzegorz Metody Sierka, PhD , Senior Clinical Embryologist ESHRE at the GYNCENTRUM Sp. z o. o. Infertility Treatment Clinic.

This innovation not only showcases AI's potential to enhance medical interventions but also highlights the shift towards a more personalized approach to healthcare.

Streamlining Healthcare Through AI

Integrating AI into healthcare goes far beyond the realms of diagnostics and treatment personalization, heralding a new era of efficiency and patient-centric care. The insights from "How to Prepare for a Bright Future of Radiology in Europe"[3] highlight the multifaceted impact of AI on healthcare management. AI-powered tools are not only revolutionizing the way medical images are analyzed and interpreted but are also significantly reducing the reporting burden on radiologists. This allows them to dedicate more time to multidisciplinary clinical tasks and patient-related activities, thereby enhancing the overall patient experience.

Technology, such as Carebot 's, particularly in X-ray and mammography, serves as a prime example of how AI supports the early detection of diseases like lung and breast cancer. By acting as a second set of eyes, their AI algorithms help radiologists identify potential issues more quickly and accurately, significantly reducing the risk of missed diagnoses. This early detection is crucial, as studies[4,5] have shown that the survival rate for lung cancer exceeds 87% when diagnosed at stage 1, compared to less than 19% at stage 4. Similarly, early detection of breast cancer increases the five-year survival rate from 25% at stage 4 to 99% at stage 1. These statistics highlight the critical role of AI in improving patient outcomes and the efficiency of care. Moreover, by prioritizing cases that require urgent attention, AI can significantly accelerate the diagnostic process, potentially saving lives by ensuring timely treatment initiation.

By seamlessly integrating AI solutions into existing diagnostic workflows, healthcare professionals can leverage these advanced tools without the need for additional programs, streamlining the diagnostic process and ensuring that every patient receives the highest standard of care.

Furthermore, these advancements are facilitating a shift towards patient-centred care, where radiologists can engage more directly in consulting roles, offering their expertise in tumour boards and multidisciplinary team meetings. This evolution underscores the potential of AI to streamline healthcare operations, making the entire system not just more efficient but also more responsive to the needs of patients and medical professionals alike.

Expanding the Horizons of AI in Healthcare

Under the leadership of Professor Peter van Ooijen , the EuSoMII - European Society of Medical Imaging Informatics is broadening its scope beyond traditional radiology to encompass a wider array of medical disciplines, including nuclear medicine and radiotherapy. This expansion reflects a dedication to interdisciplinary collaboration and education, highlighting the society's role in pioneering the integration of AI into medical imaging and informatics.

"AI has yet to be included everywhere in the medical education curriculum... AI has to be part of the medical training in the future." — emphasizes professor van Ooijen.

This statement underscores EuSoMII's commitment to ensuring future healthcare professionals are well-equipped to leverage AI technologies. By fostering partnerships across professional societies and industries, and prioritizing educational initiatives, EuSoMII aims to enhance the application of AI in healthcare, promising a future where diagnostics and therapies are more precise and personalized.

The society's efforts to grow its membership across various specialities, including a significant increase in radiographers, reflect the growing importance of AI in clinical practice. This interdisciplinary approach, coupled with initiatives like the ESR Masterclass in AI, signifies a proactive stance towards integrating AI into the healthcare continuum, ensuring that medical imaging and informatics professionals are at the forefront of this technological evolution[6].

Understanding AGI and Gen AI: Foundations for Precision Medicine

Artificial General Intelligence (AGI) and generative AI (gen AI) are two pivotal branches of artificial intelligence transforming healthcare. AGI aims to replicate human cognitive abilities, enabling machines to perform a wide array of tasks that typically require human intelligence. In contrast, gen AI focuses on creating new content, such as images, text, or data, based on its training. While AGI provides a broad understanding and adaptability for analyzing complex medical data, gen AI offers innovative solutions for generating personalized medical insights. Together, they pave the way for precision medicine, supporting tailored treatment decisions with depth and efficiency beyond traditional methods.

Harnessing AGI for Radiation Oncology

The advent of AGI in radiation oncology marks a significant milestone in the quest for precision medicine. A recent breakthrough involves the development of large multimodal foundation models that are transforming radiation oncology, offering a more nuanced and comprehensive approach to cancer treatment. These models, capable of processing vast amounts of textual and imaging data, are setting new standards for patient care. For instance, the integration of AGI models like GPT-4 and PaLM 2, alongside large vision models such as the Segment Anything Model (SAM), is revolutionizing the way we understand and treat cancer. By analyzing patient data in unprecedented depth, these models enable the creation of highly personalized treatment plans that significantly improve outcomes for cancer patients[7]. This innovation not only exemplifies the potential of AI to enhance medical treatments but also highlights the collaborative efforts between technologists and healthcare professionals in pushing the boundaries of what's possible in cancer care.

Overcoming Challenges: Balancing Innovation and Ethics

The exploration of generative AI (gen AI) in healthcare brings forth a mix of hope, hype, and hesitation. As discussed during DayOne - Healthcare Innovation 's OPEN MIC Next in Health Series[8], gen AI holds the promise of democratizing access to medical services and information, improving data access from clinical studies, and streamlining administrative tasks. However, the adoption of gen AI in healthcare is met with scepticism and regulatory hurdles, primarily due to concerns about biases and the reliability of AI-generated insights. Despite these challenges, the potential benefits of gen AI in enhancing patient care and operational efficiency cannot be ignored. For example, in radiology, AI assists radiologists in analyzing thousands of images, reducing fatigue-related errors and improving diagnostic accuracy.

Despite these advancements, integrating AI into healthcare is not without its challenges. Data security and privacy remain significant concerns, necessitating stringent cybersecurity measures. Moreover, the integration of AI technologies with existing healthcare IT systems poses substantial hurdles, requiring seamless compatibility and operation. Cultivating acceptance among healthcare professionals and patients is also crucial. These challenges are significant, but they represent steps toward a more efficient, effective, and personalized healthcare system.

This example underscores the importance of a balanced approach to AI in healthcare, one that recognizes the transformative potential of AI while also addressing ethical and regulatory considerations to ensure patient safety and trust.

The Future is Global Collaborative

In the realm of healthcare transformation, international collaborations serve as beacons of innovation and progress. Examples such as the EU's Horizon Europe program, which fosters research and innovation in digital health and AI illustrate the power of collective effort. These initiatives not only advance medical research but also encourage the sharing of knowledge and resources across borders.

The future of healthcare in CEE is undeniably intertwined with AI. Success in this new era hinges on our ability to foster international partnerships and embrace interdisciplinary collaboration. At Brainstore s.r.o. , we are committed to leading this charge, facilitating the integration of AI into healthcare to improve patient outcomes across the region.

Partnering with us opens the door to leveraging collective expertise and resources, amplifying the impact of AI in healthcare across Central and Eastern Europe. Our unique position at the intersection of technology and the world of medical practitioners, including Key Opinion Leaders, enables us to serve as a bridge for international companies looking to expand their reach in the region. By understanding both the cutting-edge developments in IT and the specific needs of doctors and healthcare providers, we facilitate seamless introductions and integrations, ensuring that innovations not only enter the market but truly resonate with medical professionals and institutions.

The revolution is underway, and its success depends on our collective efforts. Let's embrace the power of AI to create a healthcare system that is not only more efficient and effective but also more humane and personalized. The time to act is now.

Author: Micha? Matecki

Sources:

1. "Kielce/ Sztuczna inteligencja ma pomóc w radioterapii - umowa o wspó?pracy ?CO i AGH." [2023-10-23] Nauka w Polsce, PAP. https://www.nauka.pap.pl
2. "Sztuczna inteligencja wsparciem w leczeniu niep?odno?ci." [2023-10-25] Wprost Zdrowie. https://zdrowie.wprost.pl
3. Becker, M. "How to prepare for a bright future of radiology in Europe." [2023-10-10] Insights Imaging 14, 168 (2023). https://doi.org/10.1186/s13244-023-01525-3
4. McGarvey, N., Gitlin, M., Fadli, E. et al. "Increased healthcare costs by later stage cancer diagnosis." [2022-09-13] BMC Health Serv Res 22, 1155 (2022). https://doi.org/10.1186/s12913-022-08457-6
5. Carebot's AI projects: CRX - https://www.carebot.com/en/x-ray and MMG - https://www.carebot.com/en/mmg
6. "The Growing Role of AI in Radiology," DiEurope, interview with Professor Peter van Ooijen, President of EuSoMII. https://dieurope.com/the-growing-role-of-ai-in-radiology/
7. "Artificial General Intelligence for Radiation Oncology." [2023-12-20] ITN Online. https://www.itnonline.com/content/artificial-general-intelligence-radiation-oncology
8. "Generative AI in healthcare: A mix of hope, hype and hesitation." [2024-01-11] DayOne. https://www.dayone.swiss/generative-ai-in-healthcare/