Examples of Artificial Intelligence in Healthcare Worth Learning From

Everyone has their own examples of how artificial intelligence (AI) will benefit one industry or another, and healthcare is no different. But what does AI mean for this industry, and how does it impact the handling of patient queries and calls, diagnosing complex diseases, or even life-saving surgeries?

A lot has changed since 2019. Back then, our ways of working were different, and AI was on many managers to-do lists. That all changed in the early spring of 2020. Suddenly companies and industries that were moving at a snail’s pace towards implementing AI and cloud technologies into their ways of working were obligated to move faster as the world was forced to embrace remote working overnight – or risk the collapse of their business entirely. 

However, one reason this shift was surprisingly easy for a lot of companies was the lightning-quick, and clever use of AI cloud technology, which ensured all work could be carried out remotely before being uploaded to a server that colleagues or teammates had access to – automatically.  

This explosion in the use of AI and cloud technology also caused companies to start really looking at what cloud and AI technology could do for them, and one industry that has many examples of this was the healthcare sector.

Examples of AI in healthcare 

As in other industries, AI supports healthcare workers in many ways, from answering customer queries to diagnosing complex blood diseases before they even become visible. The next section of this blog will discuss the more complex and life-saving examples of AI in healthcare, but for now, let’s discuss how this technology improves the customer experience side of healthcare. However, to do this we need to – briefly – go back to 2020. 

During the pandemic stress and anxiety levels were off the charts. Understandably so for regular people worried they might be ill. But did you know levels of stress and anxiety were also extremely high for healthcare professionals during the pandemic? Talk to any doctor or nurse and you’ll discover that on the best day they’re overworked, but between 2020-22 they were almost completely overwhelmed. Which caused them to stress over the patients they might be missing amid all the panicked phone calls they were receiving.

However, this is where AI-backed large language models (LLMs) came in. By making LLM implementation a high priority, healthcare organizations – from the smallest practice to the biggest health insurance provider – were able to sort the urgent calls from the not-so-urgent ones by identifying keywords in patient responses on forms or on automated screening calls.  

This focus on keywords enabled doctors to help the people who really needed them while worried members of the public were sorted into groups, then directed to an experienced call center agent who could help them faster than agents who had less experience handling queries such as theirs. All of this resulted in less stress and anxiety for both patients and doctors across the globe during one of the most turbulent times in recent history.

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This focus on keywords enabled doctors to help the people who really needed them while worried members of the public were sorted into groups, then directed to an experienced call center agent who could help them faster than agents who had less experience handling queries such as theirs. All of this resulted in less stress and anxiety for both patients and doctors across the globe during one of the most turbulent times in recent history. 

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What’s more, this technology has been so successful in screening and managing patients for doctors that it’s still in use today. It’s even used in virtual assistants that are – in most cases – able to help patients before they even call their doctor, which of course, helps free up the phone lines for people who really need help.

How is AI used in the healthcare sector? 

However, that is just the tip of the iceberg when it comes to AI’s ever-expanding role in healthcare. It’s now also able to: 

• Assist in surgeries: AI is now being used in a growing number of heart surgeries to augment the doctors work, by giving them access to an assistant who never gets tired, is able to perform complex tasks, and even comes with a high-resolution screen that gives doctors a better view of the operating site than ever before – resulting in better surgeries, fewer complications, and higher recovery rates. 
• Diagnose blood diseases much earlier: AI-backed microscopes now make it easier to detect harmful bacteria or other bad actors in patients’ bloodstreams, thanks to the thousands of blood sample images that were fed into the AI system embedded in these microscopes. This enables them to identify problems before they cause any harm, leading to earlier, more accurate diagnoses and treatment of many once fatal blood diseases. 

• Help develop better drugs: AI also helps drug companies improve their offerings by simply scanning them and generating a report showcasing how they can be improved successfully – without sinking thousands of man hours and, potentially, millions of dollars into a new venture that might not be as successful as it first appears. 
• Provide more targeted patient treatments: Deep learning technology, meanwhile, helps provide better, more targeted treatments to patients by comparing their situation to similar patient cases, identifying patterns that have worked for others in the past, and personalizing these patterns to suit patients on an individual level – leading to higher patient satisfaction rates and more successful treatment plans in the long run. 
• Generate better scan images: AI also makes taking and deciphering complex images, such as CT scans much easier, thereby improving diagnoses and patient care immeasurably – which is especially crucial at a time when many hospitals across the globe are facing staff shortages in areas such as radiology. 
• Reduce dosage errors: in addition, AI ensures that patients are always given the right amount of drugs at the right time, thus reducing human error and ensuring no harm comes to patients as a result. 

All these benefits are in addition to all the mundane tasks AI helps automate for you and your team so that they can focus on what’s important –, caring for your patients. Therefore, if you work in the healthcare sector and have limited the rollout of AI in your organization, it might be time to rethink that strategy if you want to reap the benefits AI brings to the table, both for your organization and your patients. 

Read more: Generative AI in ecommerce

Fields where AI might be useful 

With all these examples in mind it’s safe to say that AI has found a home at the heart of healthcare. From handling basic customer queries to diagnosing diseases before a doctor can even notice them or assisting in some of the most complex surgeries known to man, AI isn’t going to lessen its role in this sector anytime soon. 

But of course, AI also has made its mark in other industries to date including: 

• Improving customer experiences by revolutionizing call centers with natural language processing to help organize queries, detect patterns and automate responses in a human-like fashion, freeing up staff to handle more urgent issues. 
• Ensuring month-end close is much easier for finance teams by accurately tracking and recording every transaction they successfully completed that month. 

• Accurately tracking the carbon footprint of many organizations’ supply chains and offering them solutions on how to reduce their impact on the environment in the months and years to come. 

Summary

In conclusion, if you want your organization to offer cutting-edge technology to your employees and market-leading healthcare to your patients then you need to keep looking for new examples of innovation that can expand AI in your business. 

Companies around the world turn to Software Mind for our experience, expertise and proven results implementing AI technologies. Contact us to find out how our cross-functional development teams can guide and drive your digital transformation strategies.

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