Generative AI Use Cases in Healthcare

Introduction to Generative AI in Healthcare

This cutting-edge technology holds the promise of revolutionizing the healthcare industry by providing healthcare professionals with precise and personalized insights, automating routine administrative tasks, and boosting patient engagement. By leveraging generative AI, the healthcare sector can achieve unprecedented levels of efficiency and effectiveness, ultimately leading to better care for patients.

Definition and Overview of Generative AI in Healthcare

Generative AI in healthcare is a specialized branch of artificial intelligence that employs machine learning algorithms to generate new, synthetic data that closely mimics real-world medical data. This synthetic data can be instrumental in training machine learning models, simulating clinical trials, and personalizing patient care. The potential applications of generative AI in healthcare are vast, ranging from improving diagnostic accuracy to enhancing treatment plans. By harnessing the power of generative AI, healthcare providers can deliver more precise and effective care, ultimately improving patient outcomes and reducing costs.

Benefits of Generative AI in Healthcare

The benefits of generative AI in healthcare are manifold, offering significant advantages that can transform the industry. Some of the most notable benefits include:

• Improved Patient Outcomes: Generative AI can assist healthcare professionals in making more accurate diagnoses and developing personalized treatment plans tailored to individual patients’ needs.

• Increased Efficiency: By automating administrative tasks, generative AI frees up healthcare professionals to focus on high-value activities, such as direct patient care.

• Enhanced Patient Engagement: Generative AI can empower patients to take a more active role in their healthcare by providing personalized insights and recommendations.

• Reduced Healthcare Costs: Generative AI can streamline clinical workflows, reducing the need for unnecessary tests and procedures, and ultimately lowering healthcare costs.

By leveraging these benefits, generative AI has the potential to revolutionize the healthcare industry, making it more efficient, effective, and patient-centric.

Despite a few challenges, generative AI is making a huge progress in healthcare. It's highly probable that it will completely revolutionize it within the next few years.

As said by Dr. Lloyd Minor, the Dean of Stanford University School of Medicine, “there has never been a better time to be going into medicine. [AI is] the most radical transformation in health since the introduction of antibiotics.”

A bold statement? Perhaps, but I think it’s by no means an exaggeration. Estimates say that, by 2032, the value of the global general AI healthcare market will reach $17.2 billion.

While over 25% of scientists believe artificial intelligence will play a crucial role in healthcare by 2033, they worry about potential shortcomings like high costs, stringent regulations, and AI hallucinations, which can cause a lack of accuracy and misinformation.

But even despite these challenges, AI researchers and medical institutions are making huge steps towards integrating GenAI across various aspects of healthcare systems.

Without further ado, here are a few capabilities of AI in the field that I find the most exciting along with examples of groundbreaking healthcare AI companies.

Restoration of lost capabilities

Since AI can be taught to not only understand but also act on different signals, it’s a great solution for restoring lost abilities such as speech or movement by analyzing patient data to turn brain waves into text or nerve signals into movement. As it improves continuously, AI in healthcare has a huge potential to revolutionize neurotechnology and rehabilitation. Some examples include:

1. Communicating via brainwaves

Researchers from GrapheneX-UTS Human-centric Artificial Intelligence Centre at the University of Technology Sydney have built a system that allows paralyzed people to communicate again. It's a cap that decodes silent thoughts and translates them into text.

It's life-changing for people who fell ill (experienced a stroke, got paralyzed, or had an accident) and lost their ability to speak. It could also be used to communicate between people and machines – think bionic hands.

2. Movement Restoration for People with Paralysis

Movement restoration for people with paralysis is a critical area of research, and generative AI has the potential to play a transformative role in this field. By analyzing data from individuals with paralysis, generative AI can uncover patterns and trends that may not be immediately apparent to human analysts. This advanced technology can be utilized in several ways to restore movement in people with paralysis:

• Developing Personalized Treatment Plans: Generative AI can analyze comprehensive data from paralyzed individuals, including their medical history, genetic profile, and lifestyle, to create highly personalized treatment plans that address their unique needs.

• Identifying High-Risk Patients: By examining data from paralyzed individuals, generative AI can identify those who are at a higher risk of developing certain conditions or experiencing adverse events, enabling proactive intervention.

• Identifying Trends and Patterns: Generative AI can sift through vast amounts of data to identify trends and patterns that may not be visible to human analysts, providing valuable insights for developing new treatment approaches.

Overall, generative AI has the potential to revolutionize the field of movement restoration for people with paralysis, leading to significant improvements in patient outcomes and quality of life.

2. Movement restoration for people with paralyzes

Bioelectronic medicine researchers, engineers, and surgeons at Northwell Health's Feinstein Institutes for Medical Research have implanted microchips into the brain of a person who suffered from tetraplegia, i.e., four limbs paralysis. They have used AI algorithms to reconnect his brain with his spine, which acted as a digital bridge and allowed the paralyzed man to regain movement in his hands and feel sensations again.

3. Bionic hand

Another case of using artificial intelligence in healthcare is the development of a bionic hand. Professor Ortiz Catalán, Head of Neural Prosthetic Research at the Bionics Institute in Australia, led research which resulted in the creation of the “highly integrated bionic hand that can be used independently and reliably in daily life”.

The hand is connected to a person's nerves and bones, with AI translating signals into hand movements. All this is possible thanks to the use of electrodes, new microsurgical techniques, and machine learning.

Personalized patient care

One of the most powerful capabilities of generative AI in healthcare is offering tailored recommendations and individual support. These relate both to offering psychological and physical care assistance, like drug use instructions.

Some examples include:

4. LLM-powered Diagnosis of Thought (DoT) prompting in psychotherapy

A group of scholars from Carnegie Mellon University and University of California have developed a Diagnosis of Thought (DoT) prompting system, which lets AI analyze patients' speech, separate emotional statements from facts, and assist psychologists in proper treatment plans.

Among others, DoT can detect contradictory thoughts to help professionals notice cognitive distortion in patients. Compared to ChatGPT, DoT prompting is a vast improvement in diagnostic accuracy.

5. AI-powered companions for senior patients

New York State's Office for the Aging is piloting ElliQ, a digital companion for elderly patients. Intuition Robotics, the creators of the device, describe it as the “sidekick for healthier, happier aging”.

The robot acts both as a digital assistant and virtual companion. A state study from mid-2023 reports that 95% of ElliQ users agree it reduces feelings of isolation and acts as a mood booster.

NY state plans to invest another $700,000 in 2024 to offer setups, maintenance, and device security to patients under the care of the Office for the Aging.

Drug discovery and development

Synthetic medical data can be analyzed by artificial intelligence to identify patterns that humans are unable to, which comes in handy in drug development. It’s fast and accurate, which is why it is so good at spotting potential drug candidates and speeding up the drug discovery process.

6. AstraZeneca partners with an AI company to develop an alternative to chemotherapy

A leader in generative AI antibody discovery, Absci Corporation, has entered into a partnership with AstraZeneca to develop an AI-designed antibody to treat cancer. By joining forces, the two companies hope to speed up the process of developing a drug that would aid in treating cancer sufferers.

7.Improving speed and safety of drug development

Drug development takes a lot of time. But imagine if we could use AI in healthcare to represent every single cell in our bodies, i.e., a virtual cell that mimics human cells. Scientists could use such a simulator to verify how our cells react to various factors such as infections, diseases, or different drugs. This would make patient diagnosis, treatment, and new drug discovery much faster, safer, and more efficient. That's exactly what Priscilla Chan and Mark Zuckerberg are working on – a virtual cell modeling system, powered by AI.

Medical training and simulations

AI now gives medicine students and professionals access to practical training, which was previously available only on-site at the hospital, including the operating room. By participating in AI-powered training and treatment simulations, healthcare professionals can practice new skills and gain access to knowledge in an interactive, engaging setting. These technologies are often used with VR/AR headsets to further mimic real-life experiences.

8. Simulation-based learning (SBL) for med students

Western Michigan University is now using simulations as part of its medical studies curriculum. Students gain access to over 100 hours of simulations, which offer realistic examples of patients, facing common situations and experiencing specific symptoms.

At the university's Simulation Center, students receive feedback from professors after each fictional medical intervention.

9. Surgery simulations

Touch Surgery is one of the first simulation healthcare software of its kind. It offers access to over 200 surgical procedure simulations spanning 17 different medical specialties. These are based on recordings of real-life operations.

Clinics can also upload their own videos to the app from external drives and via integrations with laparoscopic or surgical robot systems. AI also automatically blurs patients' identities to ensure the highest security and privacy standards.

Clinical diagnosis assistance

Generative AI in healthcare offers medical professionals access to vast amounts of clinical data, which can be used to draw accurate conclusions for better diagnoses. This technology minimizes the risk of mistakes that can happen due to distractions or physical and mental exhaustion.

10. AI-powered healthcare search experience for doctors

In late-2023, Google announced that it would roll out a special GenAI search experience for healthcare professionals, which will bring all patient information into a single system. With the help of Vertex, the company's AI search platform, doctors will be able to quickly access patient records without worrying about missing any information. They'll also be able to save a lot of time by avoiding jumping back and forth between multiple platforms.

11. Pancreatic cancer diagnosis

In a study published in Nature Medicine, a group of over 35 scholars revealed that they've developed a new pancreatic cancer detection technology called PANDA. By using AI-powered screening of CT scans, they were able to spot and properly identify pancreatic cancer with an accuracy rate higher than “the average radiologist”.

PANDA provided a proper CT scan analysis of over 92.9% in cancer-positive cases and 99.9% in non-cancer cases. The AI-powered tech is now evaluated as a method for analyzing large groups of asymptomatic patients, at a very modest cost. This shows the positive economic impact of AI in healthcare.

Medical Data Analysis

Medical data analysis is a cornerstone of modern healthcare, and generative AI has the potential to revolutionize this field. By analyzing large datasets, generative AI can identify patterns and trends that may not be apparent to human analysts, providing valuable insights that can improve patient care and outcomes.

12. Analyzing Electronic Health Records (EHRs)

Electronic health records (EHRs) are a critical component of modern healthcare, and generative AI has the potential to revolutionize the way we analyze and utilize this data. By applying generative AI algorithms to EHRs, healthcare professionals can gain deep insights into patient outcomes, identify trends and patterns, and develop personalized treatment plans. Generative AI can be used to analyze EHRs in several impactful ways:

• Identifying High-Risk Patients: Generative AI can analyze EHRs to identify patients who are at high risk of developing certain conditions or experiencing adverse events, enabling early intervention and preventive care.

• Developing Personalized Treatment Plans: By examining a patient’s unique medical history, genetic profile, and lifestyle, generative AI can develop personalized treatment plans that are tailored to the individual’s specific needs.

• Identifying Trends and Patterns: Generative AI can analyze EHRs to uncover trends and patterns that may not be apparent to human analysts, providing valuable insights that can inform clinical decision-making and improve patient care.

Overall, generative AI has the potential to revolutionize the way we analyze and use EHRs, leading to significant improvements in patient outcomes and healthcare efficiency.

Public health support

As I mentioned previously, AI in healthcare plays a major role as it can quickly process large data volumes and derive insights from it. No wonder it's a great fit for public health support. It's able to predict and anticipate potential public health issues such as disease outbreaks and act as a warning system.

12. Generating insights in minutes to prevent disease outbreaks

To avoid problems related to health, economy, and society caused by outbreaks, it's key for both the private and public sectors to have access to unbiased, accurate data in real time. In the past, it took days to generate such data. Now thanks to the tool developed by BlueDot it takes minutes. By using solutions like Cohere Classify and Cohere Rerank they have developed an interactive interface based on natural language processing to provide users with infectious disease intelligence fast.

Preventing illegal drug trafficking

The abuse of illegal drugs such as fentanyl has become more prevalent, especially in the US. Many of these narcotics are smuggled across the border from Latin America. Altana has broadened its collaboration with the US Customs and Border Protection (CBP) to stop illegal drug trafficking. CBP will use Atlana's AI-powered, dynamic map of the global supply chain to spot companies that might be linked with illegal fentanyl production across the global value chain. This should help in developing trusted global supply chains and limit drug trafficking.

Automating administrative tasks

The role of generative AI in healthcare must also be recognized when it comes to administrative work and operations. It helps professionals in the field find information more easily and avoid a lot of manual work. This, in turn, reduces the risk of mistakes.

14. Reducing inefficiencies in healthcare

GE HealthCare and Mass General Brigham have entered into a partnership in an effort to co-create an AI algorithm that will improve the effectiveness and productivity of medical operations. Firstly, they'll work on the schedule predictions dashboard of Radiology Operations Module (ROM). It's a digital imaging tool that is meant to aid in schedule optimization, reducing costs and admin work and allowing clinicians to have more time with patients.

15. Medical imaging data analysis

Amazon revealed that they were introducing an AWS-based, AI-powered health imaging solution that enables large-scale medical image storage, processing, and analysis. Medical professionals can use a single image stored in the AWS cloud as the ‘master file' source for their historical and current data.

According to Amazon, the HealthImaging app shows the potential positive economic impact of AI in healthcare. They claim that the costs associated with medical image-storing apps, which are one of the essential healthcare software types, can be brought down by 40%.

Generative AI is set to transform the healthcare field

As the examples I've shared perfectly demonstrate, access to AI in healthcare has been heavily democratized. Not all types of AI implementations require hundreds of thousands of dollars in implementation and costly hardware.

While the technology behind GenAI tools is sophisticated and innovative, and developed by many of the world's leading technology experts and scientists, it can be used by those who aren't as tech-savvy.

I think that if there is one sector where AI can make a massive difference, and where its potential can be shown to the fullest, it's healthcare. Not only can it help people who lost the ability to move or speak regain it, but also prevent disease outbreaks, reduce the use of illicit substances, and accelerate drug discovery. If you're looking to explore how AI can help your life science or digital healthcare project, reach out – our team at Netguru would be happy to discuss how we could support you in this journey.