Artificial intelligence must work for us all

mike hedges – Guile Abertawe

We are currently in the midst of the fourth industrial revolution, the artificial intelligence (AI) revolution, which builds on the ICT revolution of the 1980s. This must be a societal benefit for all of us, not just the rich and powerful.

We are witnessing fundamental changes in the way global production and supply networks operate, not only in the continued automation of traditional manufacturing and industrial practices using modern technology, the Internet, and large-scale machine-to-machine communication, but also in the use of machine learning to perform some technical tasks better than humans.

This allows for improved communication, increased automation, increased self-monitoring, and most importantly, the use of smart machines that can analyze and diagnose problems without the need for human intervention.

Machines have been improving the efficiency of humans performing repetitive tasks for years, performing tasks faster and more consistently than humans, from spraying cars to automated accounts.

Combining machine learning and computing power enables machines to perform increasingly complex tasks.

AI has wide applications in all sectors of the economy. Advances in deep learning gained traction in the 2010s, when computers began beating grand masters at chess, solving Sudoku faster than humans, and eventually beating experts at Go.

That influence was further intensified in the early 2020s with the rise of generative AI, where models can have verbal and textual discussions and analyze images.

One area where artificial intelligence can be used to improve productivity, efficiency, and outcomes is health.

Healthcare costs are rising due to patient treatment costs and drug costs. This is an area where AI can help improve efficiency and algorithms can analyze medical images, patient data, and other information to help diagnose disease and detect patterns and correlations that humans might miss.

stroke

AI can help diagnose lung cancer more accurately and predict heart attacks and strokes more effectively than medical professionals.

We have publicly reported that the application of AI algorithms in fields such as ophthalmology has improved the accuracy of glaucoma and cataract screening and diagnosis.

Published research shows that AI can help create treatment plans tailored to individual patient needs, taking into account factors such as a patient’s specific condition, genetic makeup, and other relevant information.

In a study by Yu et al., AI software differentiated between primary lung adenocarcinoma and squamous cell carcinoma using quantitative histopathological features collected from 2,186 full-slide pathology photographs from the Cancer Genome Atlas.

In a multicenter, non-interventional study involving 120 pulmonologists from 16 hospitals in five European countries, Topalovic et al. showed that AI outperformed pulmonologists in interpreting pulmonary function tests.

surgeon

Pulmonary function test pattern identification by a pulmonologist met recommendations in 74.4% of cases and provided an appropriate diagnosis in 44.6% of cases. On the other hand, AI accurately matched the interpretation of PFT patterns 100% of the time and made the correct diagnosis in 82% of cases.

Research shows that AI-powered devices allow surgeons to perform minimally invasive surgeries with greater precision, reducing the risk of errors and complications.

AI is being used to optimize force during surgery, find reliable surgical margins, and even automate certain procedures.

AI-powered patient monitoring monitors a patient’s condition in real-time and alerts healthcare professionals to any changes that require attention.

While autonomous robotic surgery is currently reported to be a long way off, cross-disciplinary collaboration will certainly improve the potential of AI to complement surgical care.

There are already examples of robotics and neuronavigation techniques supporting minimally invasive surgery.

AI can be used for personalized patient communications, such as sending patient schedule reminders, health tips, and next step suggestions, which can improve patient engagement and adherence to treatment plans.

AI can also be used to predict which patients are at risk of frequent emergency services, allowing for earlier intervention and potentially reducing demand on emergency departments.

When people contact a financial business, the first stage is a chat with the AI, and a human operator is only introduced if the AI ​​cannot answer the question.

wales

Why can’t we use AI to create surgery lists, answer questions, and notify patients of surgery dates and times?

The last industrial revolution saw the growth of large companies such as Google, Apple, Microsoft, and Facebook.

The region around Silicon Valley is home to many major companies founded as part of the ICT-based revolution.

Our challenge in Wales is to become home to the leading companies in the AI-driven industrial revolution, including health.