Use of Generative AI in Healthcare: Use Cases with Real-Life Examples and How It Reshapes Healthcare Industry

With the advent of generative AI, most industries started availing benefits of the same. Healthcare industry isn’t an exception. Generative artificial intelligence technology is going to change the healthcare industry throughout the world.

Healthcare industry is being revolutionized by generative AI. With the help of this innovative technology, you can automate healthcare processes, increase patient care and yes ignite the healthcare research.

Here, we are going to explore the use of generative AI in the healthcare industry. You will go through the use cases with real-life examples and statistics, and how it is going to reshape the healthcare industry.

So, let’s dive deep into it.

Generative AI Facilitates Healthcare Training and Simulations

The best part of integrating generative AI in the healthcare industry is that it ignites the process of healthcare training and simulations. Days are gone when medical professionals need to rely on traditional methods to learn about different diseases and healthcare issues.

Since Generative AI Development Company can generate realistic simulations resembling several health conditions, it allows healthcare students and medical professionals to practice in a controlled but risk-free environment. With the help of this innovative technology, medical professionals can create various patient models with various diseases. It means that being a medical student, you can have a great opportunity to study healthcare diseases in patients even without going through the real-life conditions.

Do you still have various doubts about how generative AI can help medical students? You need to have a look at the real-life example.

Real-life Example

Now, let’s go through a real-life example to understand how generative AI can facilitate medical training and simulations. The prestigious University of Michigan developed a generative AI system that produces several scenarios for imitating sepsis medical treatment.

Another university called Pennsylvania University integrated a generative artificial intelligence model to imitate the spread of the notorious COVID-19. It was meant to test various interventions, assisting medical researchers to evaluate the usual impact of vaccination and social distancing on this virus.

Both universities found great results by deploying generative AI models to evaluate the impact of virus or disease on society.

Let’s have a quick look at the statistics of the same.

Statistics

• Up to 75% of healthcare students found that AI-powered models boost their learning capability.
• 80% of medical professionals claimed that AI-assisted medical training improved the patient outcomes.

Use of Generative AI in Clinical Diagnosis

Medical professionals use generative AI models for clinical diagnosis by going through medical images. These AI generated medical images provide accurate diagnoses.

Moreover, generative AI also helps in personalized medicine by creating treatment plans according to specific needs of individual patients.

Let’s have a quick look at the real-life example of how generative AI is being used in clinical diagnosis.

Real-life Example

Medical researchers or doctors use generative AI to evaluate MRI scans to diagnose Alzheimer disease with up to 95% accuracy. It means generative AI in clinical diagnosis outperforms human radiologists.

By going through this real-life example, you must have understood the importance of generative AI in clinical diagnosis. To clarify it further, you need to have a look at below statistics.

Statistics

Role of Generative Artificial Intelligence in Drug Development

One of the most important but complicated parts of the healthcare industry is drug discovery. Pharmaceutical companies always find it complicated, time-consuming and expensive to find new drugs to fight against diseases. But with the advent of generative AI technology, it has become possible to accelerate the process for discovering new drugs to fight against diseases.

Top pharmaceutical companies implement generative AI technology to discover new drugs or medicines to treat different types of critical and fatal diseases.

Real-life Example

Let’s understand it more clearly by going through a real-life example. Researchers in the USA implemented generative AI to discover and develop an effective antibiotic that depicted promising outcomes in treating antibiotic-resistant fatal bacteria.

Obviously, by adopting Generative AI in drug discovery, medical professionals have now opened a new dimension for treatment and healthcare services.

Statistics

Up to 75% pharmaceutical firms found that integrating generative AI has reduced their time for drug development.

80% of modern patients grabbed benefits from the latest treatments developed especially by integrating generative AI.

Generative AI Automates Administrative Tasks

There are various tedious but necessary administrative tasks that healthcare professionals have to deal with such as creating patient profiles, maintaining their data and writing clinical scenarios.

Now, generative AI has revolutionized the way medical professionals used to deal with administrative tasks. Contemporary healthcare systems such as hospitals and clinics have automated most of their administrative tasks by integrating generative AI.

The best part of implementing generative AI is that it helps speeding up the communication, data access, medical history, and other processes. In other words, generative AI has eliminated the unnecessary burden from medical professionals.

Apart from speeding up the administrative tasks, generative AI has also reduced the cost of the same. So, let’s go through the real-life example for the same.

Real-life Example

Now, come to the real-life example of how implementation of generative AI can improve healthcare administrative tasks with reduced cost. A healthcare unit such as a hospital can create a generative AI ecosystem to automate and speedup patient communication.

Study shows that healthcare organizations that adopted generative AI witnessed 30% reduction in their expenses on performing administrative tasks.

Statistics

• 60% of hospitals or other healthcare organizations found that the integration of generative AI has reduced their administrative costs.
• Since generative AI provides personalized patient communication, 70% of patients experienced great patient engagement.

Gen-AI Generates Synthetic Healthcare Data

The key benefit of integrating generative AI in healthcare is that it creates expert knowledge and diverse medical case studies by creating synthetic healthcare data, such as clinical scenarios and patient profiles.

Here, you need to remember that synthetic medical data is really crucial when it comes to training innovative machine learning models as well as testing or evaluating new medical applications.

This medical data helps healthcare professionals to understand the patient's medical history, disease and other details better than ever before. This way, they find generative AI very useful in prescribing medications.

Real-life Example

Contemporary medical researchers in the United States used Gen-AI to generate synthetic healthcare data for simply training MLMs (Machine Learning Models). Thus, they found up to 25% improvement in their AI model accuracy.

Let’s understand it better by going through the statistics below.

Statistics

• 80% of medical researchers report enhanced model accuracy especially by using synthetic healthcare data.
• 75% of hospitals or other healthcare organizations report decreased data collection expenses using Gen-AI.

Generative AI - Reshaping the Healthcare Industry

Generative AI has emerged as the boon for the healthcare industry. Integrating an innovative Gen-AI framework at a healthcare organization can streamline its everyday process.

Let’s have a quick look at how generative AI is reshaping the healthcare industry.

• Drug discovery as well as development.
• Personalized medicine.
• Predictive analytics to forecast disease outbreaks as well as patient deterioration especially using patient historical data and actual-time inputs.
• Medical imaging analysis.
• Clinical trial medical research.
• Robotics and innovative prosthetics.
• Mental health support.
• Round the clock health monitoring.
• Automation of tedious medical administrative tasks.
• Improving efficiency of healthcare tools, devices and machines.

Final Words

So, generative AI is the most important technology for the modern healthcare industry. Adopting generative artificial intelligence technology to healthcare increases efficiency, accuracy and diagnosis results.

It has become easier to discover medicines to deal with different types of fatal diseases. Moreover, integrating generative AI to healthcare devices brings more accurate results, imaging and scanning. This way, medical professionals are able to perform their job better.

Ultimately patients get great benefits out of innovative Generative AI in the Healthcare Industry.