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AI in Healthcare: An Informative Guide

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AI in Healthcare: An Informative Guide

From the largest pharma giant to the smallest private practice, AI can boost efficiency and improve results

Artificial intelligence (AI) is not a fad — it’s the future. In every corner of the industry, people are finding ways to use AI in healthcare. They’re accelerating pharmaceutical research times. They’re automating administrative tasks. They’re even running appointment scheduling through a chatbot. The results so far are impressive, saving both time and money.

If you’re curious about AI in healthcare, you’ve come to the right place. This guide will run through many of the ways this tech can benefit the industry, how it’s doing so already, and where it’s all headed next.

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What is AI?


The term "artificial intelligence" first appeared in 1956, when computer scientist John McCarthy defined it as "the science and engineering of making intelligent machines." Science fiction aside, AI today refers to computer systems that can perceive their environments in some way and react accordingly.

    Two types of existing AI

    AI experts at IBM categorize existing AI technologies (which is to say AI that exists in the real world today, and is not theoretical) thusly:

  • Reactive Machine AI: A bot that uses designer-supplied data to produce an output with the greatest chance of success. RMAI is useful for parsing lots of info but can't learn over time.
  • Limited Memory AI: A bot that can recall a limited number of past events and outcomes. LMAI can adapt to new demands and improve over time.

AI in healthcare applications

Administrative work

Providers are at their best when they're treating patients. All the clerical work of operating a practice can get in the way of that. With RMAI, much of that work can be automated. Using high-quality scans, RMAI can identify different types of documents, sort them, and tag them automatically. It can also pull key info from scans and use it to populate digital records.

Note taking

Trust is the foundation of the patient/provider relationship. It can be hard to establish when the provider has to split their attention between the patient and note-taking efforts. AI lets the provider transcribe conversations with patients automatically. That leads to more complete notes without impacting bedside manner.

Care availability

Patients often have questions outside business hours, but running 24-hour phone support isn't realistic for most practices. AI in healthcare can make chatbots available for simple patient questions. However, these chatbot answers must steer clear of diagnosis and definitive medical advice.

Read more about AI and machine learning in healthcare in What Is AI in Healthcare?

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Benefits of AI in healthcare

AI in medicine and healthcare is a broad category. It can cover collating data, analyzing patterns, and even imitating human speech. In general, wherever large, repetitive data sets appear, AI can speed up their processing. That leads to faster research, better decision-making, and more efficient operations.

    AI and ethics

  • The US has no legal framework for the use of AI in healthcare
  • President Joe Biden started the process with an executive order, signed in October 2023
  • Best practices suggest as much transparency with patients as possible

How three medical industries benefit from AI

Managed care

By quickly cross-referencing a wide range of data, AI can quickly put forth possible diagnoses. AI can read vital signs, lab results, MRI scans, and X-ray studies faster than humans. It can then suggest treatment plans. However, it's critical that providers check the AI's conclusions and retain final say on treatment.


AI could mean drastic changes for pharmaceutical research. Whether it's modeling protein folding or analyzing critical trials, AI can speed up new research. It can also help discover new uses for existing drugs. However, researchers who use it must pay special attention to cybersecurity when handling patient data.

Healthcare facilities

Many companies in the medical industry use patient-facing AI chatbots. These bots can answer simple questions, collect patient data, and schedule appointments for patients. That saves time for front-office staff and opens scheduling up to after-hours requests.

Read more about the advantages of AI in Benefits of AI in Healthcare Across 4 Medical Industries.

How AI is used today

The first instance of AI in medicine came in 1971. That's when scientists created INTERNIST-1, a computer algorithm for diagnosing patients. Since then, AI has become exponentially more accessible.

    Upstream AI uses

  • Drug discovery: Pharmaceutical researchers can gauge the potential for a drug using AI. By plugging genomic data into a bot, they can predict how a drug will affect patients. That can save them from fruitless research.
  • Equipment manufacturing: The FDA has approved nearly 700 AI-enabled medical devices for sale. These tools help with everything from clinical chemistry to microbiology.

AI in treatment

Assisted diagnosis

Modern AI can use cloud computing to examine colossal data sets. By comparing that data against a patient's medical history and imaging, it can arrive at a likely diagnosis faster than the average provider. Today, AI can achieve detection accuracy of up to 99% for certain types of ailments, such as chronic kidney disease.

Treatment planning

To design a treatment plan, providers have to consider broad patient characteristics. They then refine treatment over time. That means patients may face potentially harmful and unnecessary side effects. AI can compare each patient to thousands of previous cases, resulting in better-personalized treatment more quickly.

Medical robots

Robots have wide-ranging applications in medicine. Surgeons can program them to do specific tasks in the operating room. Smart prostheses can adapt to their user's biology and movement over time. And elderly patients can use companion robots that learn behaviors over time.

Companies using AI in healthcare

AI in healthcare is more than theory or academics. A growing number of companies have recognized AI's potential. Now, they're using it to empower the entire industry. From research through diagnosis, these businesses are bringing AI solutions to life. That's critical when the sector as a whole faces resource shortages.

    Refining data

  • Before medical data can be used for research or diagnosis, it needs to be anonymized, standardized, tagged, and sorted, which can be achieved with AI
  • Swiss startup 4Quant created the HICCAP Annotation Platform for providers to quickly and continuously create curated data in the clinical setting.
  • Enlitic's ENDEX AI transforms medical imaging data into standard clinical nomenclature. That accelerates reporting, improves study routing, and makes sure providers have the info they need in time to make a decision

Research and diagnosis


NuMedii uses its Artificial Intelligence for Drug Discovery (AIDD) to make new connections between existing drugs and diseases. To do so, it uses machine and deep learning. That accelerates treatment discovery and saves on research and development. AIDD can also identify subsets of patients that respond better to specific treatments. That results in better patient outcomes.


SkinVision puts skin cancer detection in patients’ hands. Patients use the SkinVision app to photograph marks on their skin. An AI then builds a risk profile for the patient. If it spots danger, it can flag it for the patient and recommend next steps for diagnosis and treatment. The algorithm can improve over time as more and more patients participate.


Full-body magnetic resonance imaging (MRI) scans are usually costly and time-consuming. Ezra aims to lower those barriers to entry with its AI, Ezra. Ezra scans use AI to enhance images. That lowers costs and shortens scans, which empowers more patients to get scanned. And more scans means more diseases can get caught early.

Read more about the companies pushing AI in healthcare forward in 5 Companies Bringing AI Solutions in Healthcare to Life.

AI and healthcare economics

One of AI's key advantages is the speed at which it can work. Whether it's parsing huge data sets or automating clerical work, AI can save human workers incredible amounts of time. All that time saved can add up to a lot of new productivity, drastically changing the economics of healthcare. These changes are already underway. As AI grows, so too will its impact.

    AI and data security

  • Administrative automations handle sensitive patient records. Training AI models requires vast amounts of data.
  • That data must be ethically sourced, carefully protected, and, often, anonymized.
  • Department of Health and Human Services (HHS) Office for Civil Rights (OCR) reports 133 million medical records were exposed by data breaches in 2023.

Angles, investment, and impact


Among AI's many applications, two in particular stand out for the efficiency-minded. One is the ability to automate repetitive tasks, which could reduce the cost of administering an office. The second is to find opportunities for increased efficiency. Medical image analysis, for example, would allow providers to reach diagnoses more quickly. They would then be free to do other high-value tasks.


Research published in 2019 indicates that three-quarters of large healthcare organizations had already invested over $50 million in AI. Among mid-sized organizations, nearly all (95%) had invested. These numbers are expected to grow even higher, as 73% of all healthcare organizations planned to increase their investment in the coming years.


Organizations that have already invested in AI may see a significant windfall in savings. Experts estimate AI will save the American healthcare industry between $200-$360 billion. A large portion of that will come through administrative improvements. In Europe, the estimates fall between €170-212 billion.

Read more about AI’s economic implications in What Will Be the Economic Impact of AI in Healthcare?

Where is AI in healthcare headed?

Current uses for AI in healthcare are exciting. But the future of this technology is even brighter. The World Health Organization (WHO) identified five areas of interest for AI:

  • Diagnosis and clinical care
  • Patient-guided use
  • Administrative and clerical tasks
  • Medical education
  • Scientific research

In all cases, the WHO advises caution. Large language models (LLMs) can provide inaccurate results. Their users need to stay wary as the technology improves.

    Improving outcomes

  • Diagnosis and clinical care: AI has already shown its value as a diagnostic tool. But UC San Diego is pushing the tech further with COMPOSER. This AI uses deep learning to monitor patients at risk of developing sepsis. It tracks over 150 variables and flags irregularities for a physician to review.
  • Patient-guided use: Patient-facing healthcare portals are increasingly common. Data scientists suggest an AI chatbot in these portals could help patients estimate costs, find care, and review treatment options. Existing bots struggle with accuracy, leaving room for future improvement of the technology.

Empowering researchers and providers

Administrative tasks

As much as 30% of healthcare spending goes to administration. AI has the potential to increase efficiency in these repetitive tasks. Cedars-Sinai, for example, aims to use it to analyze OR usage and optimize scheduling. That could raise effective use rates and lower effective costs.

Medical education

The speed with which AI and LLMs process data may help medical students look for specific information. That can change the focus of testing from rote memorization to critical thinking.

Scientific research

Understanding how human cell types interact can help cure and treat diseases. Projects such as the Human Cell Atlas use AI to analyze massive data sets. Machine learning allowed the initiative to map human lung cells from more than 2.4 million cells. That opened the door to new potential therapies for several diseases.

Read more about where AI is headed What Is the Future of AI in Healthcare?

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