How Artificial Intelligence Is Revolutionizing Healthcare: Key Uses & Benefits

By now, everyone knows that artificial intelligence (AI) is a trending technology that’s changing the world. One of its biggest applications is machine learning (ML), and these tools are creating a significant impact in healthcare.

AI has greatly enhanced data analytics in healthcare, leading to improved accuracy and speed in data processing, diagnosis, prescription, treatment, and more. According to insights from IBM, studies suggest that AI can perform just as well or even better than humans at some healthcare-related tasks. These developments are life-changing for healthcare practitioners and patients alike.

With continued momentum, AI can do so much to transform the healthcare industry. According to MarketsandMarkets Research, the global market size for AI in healthcare in 2024 is at $20.9 billion. By 2029, it’s estimated to reach $148.4 billion, which speaks to the market’s potential. As for the industry’s biggest supporters, North America holds the largest share with 59.1%, according to Market.us.

All this goes to show that the future is headed toward a healthcare system powered by AI. This article covers the different types of AI in healthcare today, as well as its applications.

What Kinds of AI Are Used in Healthcare?

AI is an umbrella term referring to technology that can enable a machine or system to act or think like a human. Let’s look at AI’s different forms used in healthcare today:

Machine Learning

This is one of the most common forms of AI that essentially trains different models to identify patterns using data. In healthcare, this allows AI to process large amounts of clinical data to aid medical diagnosis and treatment, such as in precision medicine. Here are some common uses:

• Predicting which treatments are likely to succeed for a patient based on medical history and current health
• Detecting relevant patterns in imaging data through deep learning, such as potentially cancerous lesions in radiology images

Heart disease prediction can also be improved with ML models. A Springer article found that machine learning algorithms can predict heart disease with up to 90% accuracy.

Natural Language Processing (NLP)

NLP refers to the form of AI that teaches computers how to use or interpret human language. In practice, this might look like speech recognition, translation, text analysis, and other similar tasks. This helps medical practitioners with the following:

• Creating data (e.g., medical reports)
• Understanding and classifying text (e.g., organizing unstructured clinical notes for patients and transcribing patient interactions)
• Analyzing critical documents and research (e.g., pulling information from previous medical data to accurately diagnose illnesses)

Plus, with conversational AI, NLPs can answer basic patient concerns and complete transactions.

Rule-Based Expert Systems

These systems have “if-then” rules in place that provide clinical decision support for complex electronic health record (EHR) providers.

Clinical decision support is defined as a health information system that delivers specific health information to relevant people (whether it’s the medical care team or the patient) via specific channels for decision-making. These tools can process large amounts of patient data, suggest care plans, and even alert healthcare workers about potential issues such as a patient’s allergies.

Physical Robots

Robots have been present in the medical field for over 30 years. They can do a wide range of medical tasks, from repetitive functions in the laboratory to executing entire operations on their own. With AI, surgeons can control a robot’s mechanical arm through a computer console.

A study from the National Library of Medicine shows that surgeries with robot assistance lead to fewer surgery-related complications, less pain and scarring, and faster recovery.

Robotic Process Automation

This form of AI has less to do with actual robots and focuses more on inexpensive and straightforward computer programs. Automation is especially useful for repetitive administrative tasks like granting access or authorization, updating patient information, and billing.

What Are the Benefits of AI and ML in Healthcare?

According to a survey by The Health Management Academy, 47.5% of health systems use some sort of AI solution, while the rest of the respondents were considering it. The integration of AI into healthcare processes and practices has led to impressive results, such as:

• More Accurate Predictive Diagnosis and Treatment. Healthcare predictive analytics strengthened by AI may eventually be able to predict and diagnose diseases at a faster rate than most medical professionals.
• Cost-Efficient Pharmaceutical Research. Developing new drugs can reach an estimated cost of $1.3 billion per drug, according to the World Economic Forum. But with AI predicting side effects and identifying the most effective candidates for trial, Markets Insider notes that costs could be lowered by up to 70%.
• More Personalized Patient Care. Improvements in healthcare application development mean patients can expect more seamless methods for scheduling and consultation, as well as automated reminders and messages for patient care.
• Bigger Capacity for Healthcare Data Management. Data is valuable in healthcare, from patient care to drug research. AI can be trained to process large amounts of data in mere minutes, assisting healthcare workers across departments.
• Strengthened Healthcare Workforce. ADB notes that the world could have 18 million fewer healthcare professionals by 2030. However, with AI available to cover mundane tasks, the quality of healthcare can keep up with demand without overwhelming the existing workforce.

Powering Forward in Healthcare with AI

AI and ML technologies that can improve the level of today’s healthcare analytics. Now, medical professionals can make better-informed decisions and offer proactive and preventive patient care. Meanwhile, researchers can conduct studies more efficiently, saving on both time and cost. All this creates a positive experience for patients and other stakeholders.

There are many more ways AI will benefit the healthcare industry. Taazaa, a software development company, can build a AI-powered solution to address your healthcare business needs. Our custom AI development team offers purpose-built solutions for optimization and innovation. Reach out today to get a solution tailored to your concerns.