In recent years, we have seen enormous leaps in the capabilities of artificial intelligence (AI) within the medical world. One of the most impressive applications is the use of AI in recognizing and classifying lung infections, such as pneumonia, based on medical scans. Where doctors traditionally had to assess each scan manually, AI can now help by automatically analyzing whether an infection is present and, if so, determining whether it is bacterial or viral. This distinction is crucial for proper treatment.
Our colleague Dennis had already been
researching this groundbreaking technology back in 2018. For his graduation
thesis at the University of Lisbon in Portugal, he developed an AI model that
detects pneumonia and distinguishes between bacterial and viral infections.
Through the combination of genetic algorithms and
neural networks, the model worked with exceptional accuracy. The research not
only earned Dennis a cum laude degree, but also laid the foundation for future
applications in healthcare.
A Future with AI in Lung Diagnostics
The integration of AI in medical image recognition means that hospitals may be able to make diagnoses much faster and more accurately in the near future. With an AI system performing an initial analysis of a lung scan, the doctor can focus on interpreting the results, rather than on the time-consuming work of scanning through images. This support is especially valuable in emergency situations, where swift action is needed to prevent complications.
How Does Such a Model Work? The model learns by analyzing thousands of lung images that have already been labeled by experts. This allows the AI to understand which patterns in the scan indicate a particular infection. This enables the model to subsequently make an independent diagnosis and distinguish between a bacterial and a viral infection. AI can pick up patterns and details that are sometimes difficult to distinguish even for experienced radiologists. In this way, the model can provide a valuable addition to the expertise of the doctor, who performs a final check and makes the ultimate diagnosis.
The Steps in AI Lung Diagnostics
- Data collection: The model is trained with an extensive set of labeled lung images, where experts indicate whether an infection is present and what type it is. This allows the AI to learn which patterns are characteristic of bacterial and viral infections.
- 2. Converting images to data: The lung images are converted into a grid of pixels, which the computer reads as a series of zeros and ones (binary representation). This data contains hidden patterns that the AI can discover.
- 3. Model training: Through neural networks and genetic algorithms, the model learns which pixel patterns indicate specific infections. After analyzing thousands of examples, the model becomes increasingly better at recognizing the characteristics of different infections.
- 4. Testing and improving: The model is tested with new images to evaluate its performance. Through feedback, the model can continue to adapt and improve.
What Does This Mean for Healthcare?
The benefits of AI in diagnostics, particularly for pneumonia, are promising. Here are some important ways in which AI can positively transform healthcare:
- · Faster Diagnoses: With AI, diagnoses can be made almost instantly, which can make an enormous difference for patients who need acute care. What currently sometimes takes days could happen in real-time with AI in the future, allowing patients to receive help faster.
- · Increased Accuracy: Studies show that AI models, combined with the expertise of doctors, often work more accurately than when doctors work alone. By recognizing complex patterns in lung images, AI can help increase the chance of a correct diagnosis and reduce unnecessary follow-up examinations.
- · Cost Savings in the Long Term: Although setting up AI systems is costly, they can actually save costs in the long run. Faster and more precise diagnoses lead to more efficient treatments and shorter hospital stays.
- · Support for Doctors, Not a Replacement: A common concern is that AI will replace doctors, but AI serves more as a valuable assistant. The model gives doctors the ability to do their work faster and with greater confidence. The responsibility and interpretation, however, remain with the human.
- · More Focus on Personal Care: AI can take over routine work from doctors, allowing them more time for direct patient care. This means more attention can be given to the unique needs of each patient, improving the quality of care.
The Future of AI in Healthcare
Recently, an article appeared (https://eenvandaag.avrotros.nl/item/ai-is-beter-dan-de-radioloog-hoe-kunstmatige-intelligentie-eerder-kanker-opspoort/) about the use of AI in detecting cancer, indicating that these technologies are getting ever closer to practical application. Although AI for lung diagnostics is not yet applied everywhere, the benefits point to a promising future. Naturally, implementation brings challenges, such as data privacy, costs, and adaptation by medical staff. But as hospitals increasingly embrace AI and collaborate with data experts, this could revolutionize the way diseases are diagnosed and treated.
AI in healthcare is still in its infancy, but the potential is enormous. This technology can make the entire healthcare sector more efficient, more accessible, and more patient-centered. The example of Dennis' research shows how AI can make a concrete contribution to healthcare. With the right collaboration and support, AI can help not only doctors, but also patients in their pursuit of optimal care.
Conclusion: The future of AI in diagnostics is promising, and with the right support and adaptation, this technology can have a positive impact on our healthcare system. As AI models become increasingly smarter and more reliable, we are getting closer to a world where AI supports doctors in providing the best possible care to every patient.