Leveraging AI can deliver value and transform healthcare, says Professor Stefan Zohren, co-founder of Favom
In the dynamic world of healthcare, the need for innovation and efficiency has never been greater. By leveraging AI Machine Learning, healthcare organisations can make data-driven decisions, anticipate future challenges, and deliver exceptional care. With this knowledge as a backbone, we can understand healthcare data, glean insights and implement proactive measures.
For Stefan Zohren, Oxford Research Fellow and Turing Fellow at the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, the powerful benefit of artificial intelligence across every sector is all too obvious.
By harnessing the vast potential of large healthcare data sets, AI provides a comprehensive understanding of complex healthcare dynamics.
Stefan’s Oxford research is focused on applied machine learning in finance, economics and natural sciences, including deep learning, reinforcement learning, network and NLP approaches. At the Oxford Internet Institute Stefan teaches the intensive module on Machine Learning and the elective on Applied Machine Learning as part of the MSc in Social Data Science. He is also a fellow at the Alan Turing Institute.
Through Favom, the company he cofounded five years ago, Stefan is swiftly demonstrating the astonishing capabilities of AI. Favom developed a bespoke platform capable of connecting, assessing and deploying a series of AI algorithms across multiple databases for the London AI Centre, which comprises a number of leading healthcare institutions. By applying layered AI capabilities in order to better understand specific conditions and patterns within large healthcare datasets, Favom can now offer unparalleled possibilities that are already transforming the way clinicians and healthcare organisations can make rapid changes and effective cost savings in healthcare delivery.
Maternity Care
AI and Machine Learning (ML) technology applied across large healthcare data sets enables real-time nudging and the creation of intuitive dashboards, empowering healthcare providers to take pre-emptive actions and resolve potential issues before they escalate. “Leveraging AI in healthcare is not about replacing the human element; it’s about augmenting our capabilities,” Stefan says.
Worldwide only 4 per cent of women give birth on their Estimated Due Date (EDD). Estimated Due Dates (EDD) are used to inform clinicians and patients of the expected day a baby will be delivered. No solution today currently predicts EDD with any real accuracy. Liverpool Women’s NHS Hospital (LWH) data shows 25 per cent of resources are allocated inefficiently, estimated conservatively at an annual £25m cost, representing 185,000 employment hours.
Favom’s AI solutions are helping to solve this issue by using modern AI techniques and established partnerships to present clinicians and patients with significantly more accurate patient-specific EDD profiles. This can indicate whether a baby is expected to be pre-term or not, which has huge ramifications if both clinicians and patients are not prepared for the pre-term birth. Hospital resource allocation is heavily driven by EDD and clinical interventions are often based on inaccurately calculated due dates. Their current modelling has moved the predictive accuracy from 4 per cent to 36 per cent and accurately predicted pre-term births to 88 per cent.
Eye Care
As Stefan says: “The NHS’s journey with AI shows us that we can enhance diagnostics, personalise treatment, and ultimately, save more lives.” For eye care services, Favom’s AI technology delivers:
• Disease Detection: Early identification of eye conditions, facilitating prompt treatment and better preservation of vision.
• Treatment Personalisation: Customised treatment recommendations based on patient-specific data, enhancing the effectiveness of care.
• Operational Efficiency: Streamlined scheduling and resource management, minimising delays in critical eye care services.
Spend Data Analysis
Favom’s expertise extends to financial aspects with spend data analysis:
• Cost Reduction: Identification of cost-saving opportunities without compromising on care quality.
• Budget Forecasting: Accurate predictions of future expenditures, aiding in better financial planning.
• Expenditure Transparency: Clear insights into spending patterns, promoting accountability and informed decision-making.
The benefits of leveraging AI across healthcare will result in enhanced patient care with improved health outcomes through predictive insights and personalised care plans. It will also Increase efficiency and reduce costs, thanks to optimised resource allocation and spend data analysis, enabling a strategic advantage to clients thanks to the cutting-edge AI technology that evolves as they grow.
Bringing AI technology to the Middle East
“The NHS has taught us the invaluable lesson that at the heart of healthcare lies not just the technology, but the human touch,” Stefan says. “In the Middle East, we have the opportunity to blend cutting-edge AI and ML with this ethos to revolutionise patient care. In the NHS, we’ve seen how machine learning can predict patient outcomes and streamline operations. By sharing these insights with our colleagues in the Middle East, we aim to foster a global healthcare ecosystem that is more efficient, predictive, and patient-centric.”
As he observes, the collaboration between Oxford’s AI expertise and the NHS’s clinical experience has yielded transformative results. “Data is the lifeblood of AI, and the NHS’s approach to data governance and analytics can serve as a blueprint for healthcare systems worldwide, including the Middle East, to achieve excellence in care delivery, he continues. “As we engage with the Middle East healthcare sector, our goal is to deliver value that transcends borders and betters human health.”