Generative AI in Healthcare: A Comprehensive Guide for Decision Makers

Imagine a world where doctors can rely on AI to analyze medical data faster (and more accurately), or where treatments are personalized to an individual’s exact needs before they even step foot in a clinic.

Sounds like a movie scene from a sci-fi movie?

Enter: generative AI in healthcare! 

This amazing technology is changing healthcare 360 degrees and for all the good reasons! 

In this comprehensive guide, we will →

• Understand what generative AI is in healthcare
• Generative AI models used in healthcare
• Real-life examples of generative artificial intelligence models

Let’s get started!

What is Generative AI in Healthcare?

First, let’s understand the meaning of “Gen AI.

Well, to put it in simple terms, it is an advanced AI model technology that helps you to generate new content, such as text, images, audio, and videos, from existing data. 

In the case of healthcare, generative AI refers to technology that generates new solutions, ideas, and even predictions based on the patient data given to it.

In the healthcare industry, generative AI works by looking at massive amounts of medical data  like 

• patient records
• clinical studies
• research papers.

Once the analysis is done, it uses this data and patterns to create useful insights or solutions. 

How does generative AI help in healthcare?

• Speed Drug Discovery by helping doctors and scientists predict how molecules will behave and interact with each other. 
• Healthcare professionals can give Instant diagnoses by analyzing X-rays or MRIs and suggest possible diagnoses. 
• Analyzes a patient’s health data accurately and gives personalized treatment plans. 

How is Generative AI used in Healthcare? Top 8 Use Cases Explained

Generative Artificial Intelligence in healthcare is not just a futuristic concept. 

It’s already being put to work in many areas of healthcare, making it smarter, faster, and more efficient. 

Let’s see how it’s being used:

1. Drug Discovery and Development

Do you know that creating new medicine typically takes years of research, testing, and trials?

But with generative AI, scientists can speed up the process. 

Here’s how:

Generative AI can analyze huge databases of chemical compounds and medical data to predict which molecules are most likely to work as effective drugs. By “generating” potential drug formulas, AI helps researchers find promising candidates quickly. This can dramatically shorten the time it takes to bring life-saving drugs to market.

2. Custom Treatment Plans

Generative AI can create personalized treatment plans by looking at a patient’s medical history, the individual’s specific condition, like diabetes, BP, or any other medical condition, lifestyle, and genetic data.

Also you would be surprised to know that generative AI is used to cure cancer treatments-  that’s one of the ways generative AI is already shaping the healthcare industry.

3. Medical Imaging and Diagnosis

 Healthcare professionals have to go through X-rays, MRIs, or CT scans manually. Still, with Generative AI, they can read these medical images and support them by generating suggestions and insights.

For example, it can instantly analyze and point out any irregularities or signs of disease. Which helps doctors to make faster, more accurate diagnoses, especially during rushed situations.

4. AI Chatbots

The Gen AI virtual assistants can interact with patients, answer basic health-related questions, do data collection and assist with appointment scheduling. 

For instance, if a doctor is busy, the virtual assistant can analyze medical records and tell a patient what medications they should take and generate a step-by-step plan for managing their condition over time.

5. Get Ready for The Future

Generative AI can analyze vast amounts of health data from various sources, like hospitals, research studies, and even social media, within seconds. 

This can help healthcare professionals get ahead in the future and be prepared for any upcoming diseases with medications and resources. 

6.  Smart Decision Making

Doctors have a lot on their plates!

Well, we all know how hectic their workload is! 

And due to this, sometimes making decisions about complex medical conditions can be overwhelming. That’s where Generative AI steps in. 

It can act as a smart assistant that assists doctors by suggesting possible treatment options or pointing out critical information from patient records.

Related to Doctors: AI Medical Scribe and How Does it Work?

7. Healthcare Administrative Automation

Running a hospital or clinic involves a lot of paperwork and manual work. 

Generative AI can automate many of these administrative tasks by maintaining 

• electronic health records
• generating patient reports
• helping with billing processes 

This takes off the burden from the healthcare staff, allowing them to focus more on providing care.

8. Train Healthcare Professionals

Generative AI models can come up with realistic medical scenarios and simulate patient interactions. This can provide training opportunities to doctors and nurses to practice procedures, improve their turnaround time for patient care, brush up on skills, and gain experience.

Top 5 Generative AI Examples in Real Life

Now that we know what generative AI can do, let’s look at some day-to-day life examples of how it’s already being used. 

These examples show just how powerful and useful generative AI is becoming:

1. ChatGPT

One of the most popular real-life examples of generative AI is ChatGPT. It is a language model that provides human-like text based on prompts you give to it. 

People from various industries, such as customer support, content creators, and marketers, are using it to write blogs, create marketing copy, or generate ideas for stories.

2. Insilico Medicine

A company called Insilico Medicine uses generative AI to design new drug molecules. It analyzes vast amounts of data to create entirely new chemical compounds that might be effective in treating diseases like cancer or Alzheimer’s.

Once ready, they then go through clinical trials faster, saving time and potentially saving lives. 

3. Zebra Medical Vision

Zebra Medical Vision uses generative AI models to analyze medical images, such as

• X-rays
• CT scans
• MRIs

And generates potential diagnoses.

For instance, if a doctor uploads an X-ray of a patient’s chest, Zebra’s AI can generate possible conditions like pneumonia or tumors, making diagnoses faster and more accurate.

4. Tempus

Another company that is using gen AI technology for improved health outcomes is Tempus. It provides custom health treatment plans after analyzing a patient’s healthcare data, such as the genome and medical history. 

5. Babylon Health

Babylon Health is a telemedicine company that provides virtual assistants for medical consultations.
It uses the natural language processing feature provided by generative AI to provide answers to patients about their symptoms and give possible diagnoses based on their responses. (Isn’t this amazing!) 

Related Guide: How to Develop a Custom Telemedicine App?

Limitations of Generative AI in Healthcare

Like they say, every coin has two sides. 

Similarly, Generative AI models have undoubtedly shown amazing advancements in transforming healthcare, but they also come with their own sets of disadvantages. Here are the limitations of Generative AI: 

1. You Have to Upload Quality Data

For gen AI to work well, you have to feed high-quality data to it.

Why? 

Because if you train it with incomplete or inaccurate information, the results can be harmful.

2. It cannot Replace Human Feelings

Generative AI models may have large language models and could be great at processing information, but they can’t replace one thing. 

What?

Well, the empathy and care that healthcare professionals have for their patients.

3. Data Privacy is Risky

Healthcare data is sensitive, and therefore, it should be protected.

Generative AI models will be storing a huge amount of patient data, like genetic data, clinical data, medical images, etc., for training purposes.

Now, they are smart, but anybody can attack them if they aren’t built safely. And you know data breaches will risk and compromise patient privacy.

4. Continuous Training

Healthcare professionals have to take training to guide the generative AI models continuously. Because if they are not doing so, they are putting the AI tool at risk and making it vulnerable to cyberattacks. 

What Is The Future Of Generative AI In Healthcare?

Generative AI in the healthcare sector is making a big difference. 

But with this new tech, there are some things we need to be careful about. 

For example, 

• Protecting patient privacy has become super important
• Healthcare providers have to ensure fair usage and availability of this technology to everyone, regardless of their monetary status 

And, as easy as it sounds, it will take some more time till clear standards for how Gen AI will be used across the healthcare system.

Once these issues are worked out, though, we’re looking at a future where healthcare is more focused on patients, quicker, and much smarter. 

Conclusion

We have thoroughly discussed the potential benefits of generative AI in healthcare to improve patient outcomes; now it’s time for you to make the decision. 

If you are looking to build healthcare software development solutions with generative artificial intelligence technology, you should choose a reputable app development company like SolGuruz. 

SolGuruz is a leading generative AI development company that offers Gen AI development services to businesses of all sizes.

You can hire healthcare mobile app developers to build software using Gen AI. 

FAQs

1. What is the cost of developing generative AI models?

Well, the cost depends on various factors like the expertise of the company and the type of AI model you want to create. 

2. What different types of AI are being used in healthcare?

Different AI systems in healthcare are:

• Machine Learning 
• Natural Language Processing
• Deep Learning
• Robotics
• Generative AI