AI meets the Immune System

Oxford Immune Algorithmics® leverages years of research in Hybrid Artificial Intelligence model-driven causal discovery to develop the area of causal diagnostics – a progressive, explainable and traceable model-based approach to predictive medicine and immune system management.

There is a general lack of understanding of the changes in relating different immune cell types (counts/proportions and/or markers) and their associated change over time in the dynamics of as they transit moving from healthy to unhealthy states – whether related to either individual diseases, or groups of diseases (say inflammatory ones), or to ageing. In other words, the world better understands better the state of being ill rather than it does the state of sustained good health remaining healthy. The Change will come from turning health systems upside down, spearheaded and driven by the health consumer. Algocyte® helps drive this change with the superintelligent AI that its founder has created.

Superintelligence was solved by mathematicians (Kolmogorov, Chaitin, and Solomonoff) in the late 1950s in the same workshop at Dartmouth in the U.S. where the term AI was coined and the field started. This type of causal and optimal inference type of AI is a generalisation of all other AIs, including Generative AI and human intelligence. However, it was hard to exploit until recently because of the computational resources required, recalling the difficulties that neural networks once faced.

Oxford Immune Algorithmics’s founder, whose Ph.D. thesis advisor was one of those mentioned above who solved AGI, is the world leader in the implementation and validation of this generalisation of intelligence based on information and complexity theories that has found applications in areas ranging from cell and molecular biology to human and animal behaviour to business intelligence, for which the company has won several prestigious grants and prizes in the US, UK, Sweden, and the UAE.

In this interview conducted by MindMatters, Prof. Chaitin, one of the founders of computer science who provided an alternative proof based on the concept of randomness to one of the greatest achievements of human’s intellect, Gödel incompleteness theorems, related to the limitations of human understanding, explained the deep connections between complexity theory and Artificial Intelligence and praised the work of Prof. Hector Zenil, founder of OIA, for integrating these fields and advancing the power of their combination.

With more than 120 peer-reviewed papers in some of the most prestigious scientific journals, OIA’s Superintelligent inference engine, is meant to help understand the foundations of the transition between health and disease and contribute solving some of the most pressing challenges of the human condition, from antibiotic resistance to chronic inflammation to cancer.

Transforming Medicine with Personalised Healthcare Technology and Hybrid AI-driven Immune Health Monitoring

Model-Driven Causal Discovery

Practical clinical diagnosis is mostly based on statistical symptom pattern-matching. Model-based causal diagnostics powered by artificial superintelligence focuses on hybrid symbolic and generative models to find explanations of a disease’s cause.

Longitudinal, less invasive, real-time, and cost-effective immune health monitoring is hugely important for improving public health and delivering on the promise of personalised and precision medicine that can enable preventative strategies finding potential prescription gaps and enabling remote care.

Immune System Management

We have created a family of novel and interdependent remote and mobile solutions for rapid and affordable generation of personal longitudinal data using sophisticated neuro-symbolic machine learning. This is a type of super human-like reasoning that augments human doctors’ inference capabilities for hypothesis generation and differential diagnosis.

Precision-based Diagnostics

The training and inference engines behind causal diagnosis are based on novel intuitive and neuro-symbolic AI – a combination of powerful computational methods at the forefront of science developed by our founders that combine aspects of rational behaviour and neural computation.

Superintelligence

Reimagining Machine Learning for Disease Prediction:
An Intuitive AI That Thinks Like a Super Scientist

In an effort to highlight our research, the journal Nature produced this video to accompany the article published by our team led by Dr. Hector Zenil, Founder of OIA. It introduces the Causal Deconvolution technology behind our Causal Diagnostics approach to medicine and healthcare.

Immune Monitoring
The Future of Health Care

Dr. Kourosh Saeb-Parsy, OIA’s Chief Medical Office and Professor of Transplantation at the University of Cambridge, introduces Dr. Petter Brodin, a member of OIA’s Scientific Advisory Board, Professor of Paediatric Immunology at Imperial College and the Karolinska Institute. Dr. Brodin is a world authority in systems immunology that was invited to discuss his research and the future of medicine based on learning from each individual’s immune system and the clinical evidence that supports the vision and principles behind Algocyte

A selection of our publications

If you would like to learn more about Algorithmic Causal Deconvolution introduced by our Founder and behind Algocyte, watch this video and see how it can even be used to design targeted interventions

Featured in