What AI Sees Could Save Lives: The Power of Computer Vision in Infectious Disease Diagnostics

When you picture typical medical imaging, you see a doctor standing in front of a printed X-ray, or perhaps a CT scan on a computer. Until recently, the traditional role of imaging in medicine has been mostly structural, but what if we could “see” pathogens, not just physical damage that they cause?

Artificial Intelligence (AI), particularly machine learning and deep learning, is already revolutionising biological imaging across research and clinical applications. It addresses the challenges of analysing the increasingly large and complex datasets generated by modern imaging techniques like microscopy and medical imaging (MRI, CT, X-ray, pathology slides). In radiology, computer vision is already enhancing detection (e.g., lung nodules, brain bleeds), identifying trends & insights otherwise missed by human beings.

AI models can play a crucial role in saving lives by revolutionising how we diagnose infectious diseases. Here's how:

Faster Diagnosis: 

AI algorithms can analyse medical images like X-rays, CT scans, or microscopy slides much faster than humans. This allows for detection of signs of disease, almost instantly. Applying this directly to microscopy-based images of patient samples could radically accelerate infectious disease diagnostics, removing the need for amplification-based detection methods.

Impact: 

For time-critical situations, either in frontline military or at point of care in hospitals, care homes and schools - reducing diagnosis time from hours or days to minutes allows treatment to start much earlier, drastically improving patient outcomes, and in some cases, survival rates.

At Pictura Bio, our machine learning models visualise the types of disease-causing pathogens themselves. Using fluorescent labelling, microscopy and AI-based image analysis trained on thousands of real patient samples, our system can detect patterns invisible to the human eye, and provide results within a minute.

Traditional diagnostics often force a trade-off between speed and accuracy. PCR tests, while highly sensitive and capable of detecting multiple pathogens simultaneously, are inherently slow and bound to centralised laboratories, delaying clinical decision-making and potentially allowing infectious diseases to spread. 

On the other hand, rapid antigen tests like LFAs offer quick results at the point of care, but typically suffer from limited pathogen coverage and lower accuracy, increasing the risk of incorrect diagnosis. In contrast, our machine learning-based system adapts continuously with new training data, enabling rapid, accurate detection of both known and emerging threats.

Our approach using AI revolutionises point-of-care (POC) diagnostics through exceptional speed and accuracy. Machine learning and real-time image processing enables the delivery of diagnostic results in under a minute, a critical advantage in time-sensitive situations such as urgent care centres, ambulances, and front lines and within the 10-minute threshold for GP consultations. 

Furthermore, unlike traditional lab-based diagnostic methods, the Pictura Bio approach is designed to be inherently scalable and extendible for future diagnostic needs.

Moving beyond the limitations of single-target tests, vision-based diagnostic systems possess the ability to distinguish between multiple infectious agents simultaneously. This holds the potential for rapid screening for numerous pathogens at a significantly smaller cost compared to multiplexed PCR tests and being significantly easier to scale out. The power of machine learning extends to identifying unexpected or novel biological signatures within samples, offering the potential for the early detection of emerging outbreaks before they become widespread public health issues.

The integration of advanced AI into medical diagnostics is not without its hurdles. Key challenges, like navigating the complexities of supervised versus unsupervised learning models, establishing standardisation across platforms and ensuring trustworthiness of AI-driven results are all critical to clinical adoption. 

Acknowledging these complexities, Pictura Bio’s team is deeply committed to rigorous validation protocols, and extensive real-world testing. We believe that strong partnerships with hospitals (such as Pictura Bio’s partnership with NHS Portsmouth), diagnostic labs, and public health agencies are fundamental to overcoming these challenges and collaboratively building smarter, more reliable diagnostic systems for the future.

We stand at the cusp of a new era where the future of diagnostics is not merely biochemical, but computational. The Pictura Bio platform represents a part of this transformative wave of AI-powered tools, which promise not only to dramatically speed up diagnostics, but also to fundamentally expand the scope of what is possible in detecting and understanding disease. We invite collaborators, researchers, investors, and healthcare innovators to join us in building this new visual language for infectious disease detection and shaping a healthier future.