How AI and Data Management Are Transforming Cancer Care? COHM-MORE | BJCN 2024
At COHM-MORE 2024, the spotlight was on how advanced AI and data management solutions are reshaping cancer care. Our team demonstrated how our innovative approach is driving significant improvements in diagnostics and treatment, especially in oncology.
Improving Cancer Diagnostics with Centralized Data
One of the biggest challenges in oncology is managing the overwhelming amount of imaging data. Without proper systems in place, critical insights can be delayed or overlooked, impacting patient outcomes. Our system addresses this by centralizing and streamlining the management of medical images. This ensures that vital data reaches specialists faster, enabling quicker and more accurate diagnoses.
At the congress, we discussed how our solution is already helping to improve nuclear medicine and oncology workflows. By organizing and distributing imaging data more effectively, healthcare professionals can spend less time chasing data and more time focusing on patient care.
AI-Powered Precision in Cancer Detection
AI integration was another major highlight of the event. Our AI tools quickly and accurately detect anomalies, especially in early-stage cancers, where small irregularities are crucial but often difficult to spot. These tools provide real-time insights, allowing doctors to validate their findings and seek second opinions when necessary.
Several examples shared at COHM-MORE showed how AI-driven systems are identifying early signs of cancer that would otherwise go undetected. These systems help ensure that doctors have the best possible information to make timely and effective treatment decisions.
Real Impact in Bulgaria
In Bulgaria, hospitals using our centralized system have reported major improvements in diagnostic speed and accuracy. The centralized approach ensures that specialists receive critical data promptly, leading to better patient outcomes.
Supporting Teleoncology and Remote Care
As teleoncology continues to grow, especially in areas with limited access to specialized care, centralized systems play a key role in making remote diagnostics faster and more efficient. By enabling seamless collaboration between doctors, even across different locations, we’re helping ensure that patients receive expert care no matter where they are.
The system’s ability to offer second-opinion services through AI is particularly valuable in early-stage diagnoses. Doctors can quickly get expert confirmation of findings, which is especially important when small anomalies could make a big difference in treatment outcomes.
Doctor Concerns: The Need for AI Validation
One of the most engaging moments of COHM-MORE 2024 was the discussion on AI validation. Doctors raised important questions about how AI systems compare with existing clinical standards. As doctor Dimitar Kalev, oncologist noted, “In oncology, we rely on the gold standard. How closely does AI match this? We need concrete data to be sure.”
Other doctors stressed the need for detailed statistics on AI’s sensitivity and error rates. They called for clear data on false positives and false negatives to assess AI’s reliability.
SC PACS’ Approach to AI Validation
SC PACS addressed these concerns head-on by explaining how we validate AI solutions. Our process involves human oversight, where specialists review AI-generated assessments to ensure accuracy. Every AI tool we offer step on a Certified Architecture and MDR-compliant, built to meet the rigorous standards required for precise medical diagnostics.
To further build trust, we developed a simple but effective thumbs up/thumbs down system. After each diagnosis, doctors evaluate whether the AI’s findings were correct. Over time, this allows us to track how often AI is accurate, providing doctors with the confidence they need to integrate AI into their practice.
Doctors also highlighted that AI’s role could go beyond diagnostics—it could help analyze errors and improve clinical outcomes. With no perfect diagnostic test available, even experienced doctors become aware of the limitations. AI could be a powerful tool for identifying and learning from these mistakes, improving overall care.
Addressing Challenges in AI Adoption
The conference also focused on overcoming the barriers to fully adopting AI and better data management in healthcare. Another key point is the lack of standardized protocols for handling imaging data. Our system solves this by providing a reliable platform that centralizes data management.
As a conclusion COHM-MORE 2024 made it clear that AI and advanced data management are key to the future of cancer care. By improving how medical images are processed and analyzed, we’re helping healthcare professionals detect cancer earlier and treat it more effectively.
With AI-driven solutions and smarter data management, we’re enabling faster diagnoses, better patient care, and more efficient workflows. Let’s collaborate to bring faster, more accurate cancer diagnostics to your healthcare practice and drive the future of oncology together.