Artificial intelligence, or AI as it’s better known, has brought about a revolution in our lives. The technology is still in its early days, but the promises it brings are incredible. Healthcare is one of the many sectors that can transform, harnessing the power of artificial intelligence. 

Estimates show that by 2030, the global healthcare system could experience a scarcity of 10 million workers. We are talking about doctors, nurses, technicians, and emergency responders. AI can be a key player in bridging that gap. 

How? That’s the real life story we are here to tell you about today. 

Make Management Faster and More Efficient 

Improved by artificial intelligence, healthcare digital marketing lets companies make data-driven decisions. Predictive analytics guarantees marketing strategies are both powerful and efficient by spotting market trends, patient preferences, and successful outreach channels.

For instance, AI can determine the best time to send appointment reminders or health tips based on patient engagement patterns, increasing the likelihood of positive responses. Platforms like http://www.healthcaredigitalmktg.com/, therefore, can make things much easier for healthcare professionals and bring the main focus back on patient treatment. 

While meeting patients, doctors often write notes into electronic health records. But, this can sometimes feel distracting and make it harder for patients to connect with them. To avoid this, some doctors prefer to finish their notes later, often after hours at home.

We have already seen the use of AI to make patient documentation easier than ever before. Ambient AI, for example, is an AI-powered scribe that doctors can use to produce draft notes without doing any paperwork at all. The AI model will listen to the conversation between patients and doctors, and take notes accordingly. 

Ambient AI had a major influence in just ten weeks at The Permanente Medical Group in California. 3,442 doctors across many disciplines utilized it during over 300,000 patient visits, according to NEJM Catalyst. This shows that the technology is quickly becoming popular among doctors.

Ambulance management can be another tricky challenge AI can help solve. Data from the UK tells us that 350,000 people need to use ambulance services each year. Paramedics are in charge of deciding which patient gets access to the limited number of ambulances since there is an increased demand and the number of ambulances are limited. 

A sophisticated AI model can take in patient information and make this decision with more efficiency. It will take into account the severity of the case and the vulnerability of patients. 

There has already been a study in Yorkshire to assess the possibility of using AI for this particular purpose and the results have been quite encouraging. The results show that AI was able to make the right call in 80% cases when it was asked to decide which patients needed to be transferred to the hospital urgently. 

Accelerating Diagnostics 

If you watched the hit medical drama series House MD, you already know that diagnosis can be a tricky game at times. Of course, Dr. Gregory House and his team’s adventures are a bit more dramatic than real life scenarios. But doctors often struggle to reach a conclusion about the patient’s condition, when time is of the essence. AI can have a say here. 

A group of researchers tested Chat GPT 4’s diagnostic capabilities for a recent JAMA study.  They provided case descriptions and test results and asked the AI model to provide its diagnosis. 39% of the diagnosis were spot on. In 64% cases, the diagnosis was not comprehensive, but it identified the problems partially. 

At first glance, the numbers look far from convincing. But we must not lose sight of the fact that the technology is still evolving and it will only get better moving forward. The margin of error will continue to shrink, and within a few years, we might see AI delivering near-flawless diagnosis. 

So, doctors will be able to diagnose their patients quicker and address the problem promptly. 

AstraZeneca, the inventor of the Covid vaccine, has developed a new AI machine learning model. The company says the model can detect signs of a disease in patients even if the symptoms are mild or non-existent. 

Researchers fed data of half a million UK patients to the model and the model was able to make predictions with “high confidence”. 

Here’s what Slave Petrovski, the lead researcher, said about the model: 

“For many of these diseases, by the time they manifest clinically and the individual goes to the doctor because of an ailment or visible observation, that is far down the line from when the disease process began.

“We can pick up signatures in an individual that are highly predictive of developing diseases like Alzheimer’s, chronic obstructive pulmonary disease, kidney disease and many others.”

Expediting Pharmaceutical Research

Drug discovery is all about finding the right molecular formula and combination. Since this is about finding the right pattern, artificial intelligence can be a game-changer. Researchers have to go through a colossal amount of data to find the right compound. As you can imagine, AI can make the screening process much quicker and easier. 

Insilico Medicine delivered a breakthrough in February, 2022. The company rolled an anti-fibrotic drug for idiopathic pulmonary fibrosis, a critical lung condition, into phase-I human trials. Researchers used an AI model to find the compound. Insilico managed to complete the process within 30 months, which is quite fast, compared to industry norms. 

Pharmaceutical companies put in years of time and billions in funds to find the right combination. Therefore, AI can save both time and money for pharma businesses. 

Nine out of ten drugs fail in clinical trials, but AI is helping researchers improve success rates. With more efficient analytical models, pharmaceutical companies can now be more selective, identifying drugs with a higher likelihood of success in human trials and fast-tracking them to the next phase.

Clinical trials are lengthy, resource-intensive procedures. So, knowing which drugs are likely to pass this phase is a big advantage.