Recent developments in artificial intelligence are impacting several facets of healthcare, from improving diagnostics and treatment to advancing research and patient care. Among these, the potential transformation AI brings to mental health, drug discovery, GP practices, cancer prevention, and more is significant.
During times of great stress on the NHS, AI offers ways to help doctors prioritize patient care and potentially eliminate the need for invasive tests. Furthermore, AI might revolutionize drug discovery, expediting clinical trials while reducing costs. Kourtzi expressed that certain tools "could also be transformational in the search for new drugs, making clinical trials more effective, faster and cheaper."
However, challenges remain, as seen with dementia drugs like lecanemab and donanemab, where their benefits didn't justify approval costs within the NHS. Clinical trials often center on incorrect candidates, where AI might assist in improving participant selection. Kourtzi emphasizes, "If you have people that the AI models say will not develop pathology, you won't want to put them in your trial."
Kourtzi is part of an initiative to create a 'BrainHealth hub,' a collaboration effort between various scientific disciplines to address brain and mental health issues. This project seeks to bridge the tools available to engineers and scientists with the rich data held by clinicians and neuroscientists.
In primary care, AI applications could transform GP practices, according to Professor Niels Peek from THIS Institute. Technologies like 'digital scribes' may reduce clinicians' workload. He explains, "Considering that clinician time is probably the most precious commodity within the NHS, this is technology that could be transformational." Peek raises the importance of accuracy, noting the necessity to avoid errors such as 'hallucinations' when summarizing consultations.
Peek is also evaluating 'Patchs,' an AI tool for GP appointments and online consultations. Developed with GP staff and patients, it reflects a collaborative effort among designers, University of Manchester, and Patchs Health. Used by about 10% of GP practices in England, Peek stresses the importance of ensuring these technologies fit seamlessly into current systems and workflows.
When it comes to mental health for children, Dr. Anna Moore is exploring AI's role in managing referral bottlenecks. She asserts the need to involve the public when designing such systems, explaining, "The kinds of data that help us do this can be some of the really sensitive data about people." As advancements progress, Moore questions how these tools will inform referrals or suggest other supports when specialist resources like CAMHS might not be appropriate.
On fertility, Mo Vali and Dr. Staci Weiss lead 'From Womb to World,' aiming to incorporate AI into fertility diagnosis and personalized treatments. The project’s goal is to improve IVF outcomes, making the process more cost-effective and accessible. Data privacy and the responsible handling of datasets remain key considerations.
Vali highlights one of their objectives: “We're trying to democratize access to IVF outcomes and tackle a growing societal problem of declining fertility rates.” They're working with The Lister Fertility Clinic to test and refine their tools before broader implementation.
In cancer prevention, Professor Antonis Antoniou, Director of the Cancer Data-Driven Discovery Programme, foresees AI enhancing predictive models for cancer risk and detection. The programme, supported by several research organizations, seeks to develop AI models informed by expansive datasets. Antoniou emphasizes safeguards against inadvertently increasing healthcare inequalities, ensuring equity in access.
The initiatives extend to drug discovery, where Han’s research integrates quantum computing with AI. This approach offers unexpected insights in complex drug development processes. Han asserts, "We’ve shown that quantum algorithms see things that conventional AI algorithms don’t."
AI technology holds substantial promise across diverse medical fields, yet requires robust ethical considerations and collaboration across sectors to maximize benefits while minimizing risks.