AI is projected to become a $187 billion industry by 2030, and its influence is already reshaping patient care and medical practices.
Imagine AI systems capable of assessing disease risks or performing precise surgeries. And with their ability to learn over time, the potential impact is unprecedented.
Read on to learn about:
- 6 real-world AI healthcare examples
- Benefits of healthcare AI
- Who exactly is using AI in healthcare today in the real world?
6 real-world AI in healthcare examples
We’ve already gone over general use cases. But what are examples of artificial intelligence in healthcare that have real-world, actual consequences?
Let’s take a look because it’s more than you think:
1. Lindy’s AI Medical Scribe
Want to bring the best of healthcare AI to your clinic? Lindy’s AI agents can handle your medical documentation in a way no human scribe can match.
Here’s how:
- 80% reduction in charting time: Get 8 hours per week back for what matters most – your patients.
- Extremely accurate: With natural language processing that exceeds 99% accuracy, Lindy gives other AI solutions a run for their money.
- You make more money: $20,000-$45,000 increased annual earnings per doctor (clinician studies).
- Cost-effective: at just $99/mo, it’s significantly more budget-friendly than hiring a medical scribe — and it’s even more accurate.
- Beyond human capabilities: Medically tuned AI picks up on medical terms and shorthand and ensures your documentation is flawless, secure, and HIPPA compliant.
- No more time-consuming software: Seamlessly integrate Lindy with your existing systems (like Zoom or your other apps) and add customizable templates into your workflow.
Don’t take our word for it. Try it for free and see why thousands of practitioners are charting with Lindy.
Explore AI-powered, HIPAA-compliant Medical Dictation with Lindy.
2. AI in medical diagnosis: Treat diseases early
AI’s diagnostic tools are reshaping healthcare by identifying diseases earlier and more accurately.
Algorithms analyze medical images, lab results, and patient histories with the kind of precision that even the most eagle-eyed humans will miss. This means doctors can start treatment sooner, helping save lives and improve outcomes.
Here’s what’s impressive: IDx-DR is an FDA-approved AI tool created to detect diabetic retinopathy, a serious diabetes complication that can cause blindness. IDx-DR scans retinal images and flags signs of the disease without needing a specialist on-site.
This makes it ideal for rural or underserved areas where specialists are in high demand but short supply.
In the U.S. alone, around 9.6 million people have diabetic retinopathy. Early detection is crucial to prevent vision loss.
IDx-DR’s clinical tests achieved much more sensitivity in identifying diabetic retinopathy, allowing doctors to move from diagnostic to action much quicker.
AI is making waves in other diagnostic areas, too: Google’s DeepMind is developing breast cancer detection algorithms that have already shown a 5.7% reduction in false positives and a 9.4% reduction in false negatives. This breakthrough means fewer missed cases and fewer patients going through unnecessary biopsies.
Cardiology is also benefiting from AI — tools in this field go over echocardiograms for heart disease signs, a condition that impacts 121 million Americans and is rising.
3. AI surgeons: Next-level precision
Artificial intelligence also has an impact on surgery by giving surgeons much more control and accuracy for complex procedures.
AI-driven bots don’t have to deal with pesky stuff like hand tremors, helping perform minimally invasive operations with a much smaller chance of infection and shorter recovery times.
Prime example: The da Vinci Surgical System by Intuitive Surgical. This AI-powered system, which has supported over 14 million surgeries worldwide, translates a surgeon’s hand movements into precise micro-movements.
In action, the da Vinci system allows for delicate work around vital organs, helping avoid complications. Patients who go under the knife with da Vinci experience far less blood loss, shorter hospital stays, and a smoother recovery compared to open surgery.
AI is also making strides in orthopedic surgery: Take Stryker’s Mako robotic system, designed to help out in hip and knee replacements with a 94% accuracy rate.
By tailoring each procedure to a patient’s unique anatomy, the Mako system can get patients better-fitting implants and longer-lasting results after a big ouchie.
This precision cuts down the need for revision surgeries, helping patients recover faster with fewer complications.
4. AI in patient monitoring and virtual care: Continuous support
AI monitoring and virtual care tools keep healthcare providers connected to patients, even when they’re at home.
For those people managing chronic conditions, continuous monitoring can prevent medical crises by catching signs of trouble early.
These tools track real-time health data, sending alerts for potential issues to get you that all-too-critical health on time.
A standout in virtual care: Babylon Health is an app that lets patients check symptoms, get treatment advice, and consult a doctor over video. The app’s AI goes over symptoms, suggesting possible causes and guiding patients on what to do next.
Babylon has partnered with the UK’s NHS, reaching millions with its virtual healthcare services. In terms of accuracy, Babylon’s algorithms boast an 85% success rate in diagnosing common conditions — comparable to human physicians.
Wearable technology is also transforming patient monitoring: Devices like Fitbit, Apple Watch, and BioIntelliSense track vitals such as heart rate and oxygen levels, sending data directly to healthcare providers.
Some of these wearables can detect early signs of arrhythmias or even sleep apnea, helping prevent emergencies. Studies show that remote monitoring can cut readmissions by 38%, a critical benefit for people managing chronic diseases.
5. AI in medical imaging: Spotting details the human eye misses
Medical imaging is a vital tool in diagnosis, but it doesn’t mean it’s magical. Even with the best training, radiologists sometimes miss important details that could make a huge difference in a patient's health.
AI in medical imaging is changing this, with machine learning models trained to pick up details in X-rays, CT scans, and MRIs that can slip past the human eye.
Mind-blowing example: Viz.ai developed an AI platform that analyzes CT scans in real-time to detect signs of stroke, alerting neurology teams immediately.
Stroke is a top cause of death and disability, and each minute matters for saving lives and reducing complications. In action, Viz.ai has cut time-to-treatment by an impressive 22.5 minutes, a major advantage that is a huge benefit for survival rates.
Cancer detection is another major win: Lunit’s AI mammography model detects breast cancer up to six years earlier than traditional screening methods. How’s that for an improvement?
It also improves accuracy by reducing false positives by 5.7% and false negatives by 9.4%, meaning fewer unnecessary procedures and more lives saved (Nature). With this extra set of eyes, AI helps radiologists make faster, more informed calls on tough cases, improving patient outcomes and cutting healthcare costs.
6. AI in drug discovery and development: Faster new treatments
Bringing a new drug to market is a huge investment, often taking over a decade and billions of dollars — all good, but we need faster cures.
AI is fast-tracking this process by going over mammoth datasets, predicting drug interactions, and identifying potential treatments with much more precision. This tech means researchers can move from ideas to clinical trials in record time, saving money and lives.
Leading the charge: Companies like Exscientia and Insilico Medicine are pushing AI to transform drug discovery. Exscientia’s AI developed a new drug for OCD and got it into phase-1 clinical trials. Insilico’s AI identified a promising treatment for fibrosis, which then passed clinical testing.
In an industry where 90% of drug candidates fail, these AI tools can be a game-changer.
Cost benefits of AI: Developing a new drug costs around $2.6 billion on average, but AI could potentially reduce these costs.
Accenture estimates that AI’s impact on drug development could save the U.S. healthcare system $150 billion annually by 2026. These savings mean faster, cheaper access to new treatments for patients, plus the ability to personalize drugs based on a person’s unique genetic profile.
Healthcare benefits from artificial intelligence
Healthcare AI is already bringing a host of benefits with it, such as:
- Healthcare is more accessible: The advancement of AI in healthcare has the potential to broaden access to care and diminish healthcare costs.
- Macro and micro-level data analysis: AI's ability to process vast amounts of health data helps identify patterns, leading to enhanced diagnoses and targeted treatments.
- Better disease detection: AI systems match human physicians accurately in detecting certain cancers and eye diseases. In some cases, they’re already beating them!
- Optimizing treatment options: AI helps doctors choose the most effective treatment plans by considering patients' unique health histories and conditions.
- Nurses are now virtual: AI-powered virtual assistants offer round-the-clock monitoring and support, which is necessary for chronic conditions such as diabetes or heart disease.
They also provide health information and medication reminders and alert professionals to significant health changes.
- Support for patients in remote areas: AI extends critical health services to remote regions, offering timely interventions when in-person doctor visits are not possible.
- Admin more streamlined: By automating administrative tasks like paperwork, billing, and scheduling, healthcare AI enables providers to focus more on patient care and less on tiresome bureaucratic processes.
- Minimizes dosage errors: AI tools, analogous to household devices, could monitor and alert users of misuse or errors in medication usage.
- AI stands as a vigilant guard against financial abuses: Healthcare fraud escalates costs to an estimated $455 billion annually. By analyzing patterns in insurance claims, AI can uncover irregularities, from exaggerated billing to unnecessary testing, essentially safeguarding against practices that inflate medical expenses for consumers.
Who is using AI in healthcare in 2024?
Many major tech companies and healthcare organizations are investing in and implementing AI.
Some of the biggest players leading the charge include:
- IBM Watson Health: IBM is using AI to help identify health risks, diagnose diseases, match patients with clinical trials, and more. Their AI systems are already deployed in major hospitals and health systems around the world.
- Google DeepMind: DeepMind has collaborated with the UK's National Health Service to develop AI that can analyze CT and MRI scans to detect abnormalities. They’ve also created AI models that predict acute kidney failure and help out with other medical predictions.
- Microsoft: Microsoft partners with healthcare organizations to apply AI for administrative jobs like revenue cycle management and clinical use cases such as analyzing EKGs and detecting diabetic retinopathy.
- Philips: Philips has developed AI-enabled devices and software for use in hospitals and at home. This includes systems that analyze CT scans to detect COVID-19 (remember that whole mess?) and AI tools that help clinicians monitor ICU patients.
- NVIDIA: Nvidia’s AI platforms for radiology, pathology, and genomics are widely used in healthcare. Their AI helps detect anomalies in medical scans, analyze tissue samples, and derive insights from genomic data.
- Tempus: With a huge focus on precision medicine, Tempus uses AI to analyze clinical and molecular data, helping oncologists personalize cancer treatments based on genetic information.
- Butterfly Network: The company combines handheld ultrasound devices with AI to provide real-time imaging assistance, making ultrasound more accessible and actionable across different healthcare settings.
FAQs
What types of tasks can AI help automate in healthcare?
Healthcare AI has the potential to automate tasks completely like:
- Processing medical records and insurance claims
- Managing patient schedules and coordinating care
- Monitoring patients and vital signs
- Transcribing notes and diagnosing certain conditions
Can AI replace doctors and nurses?
Not really — and it probably won’t any time soon. AI for healthcare is meant to enhance tasks, not replace human roles. Sure, it can handle routine stuff and data crunching. But, decisions that need empathy, critical thinking, and good old-fashioned judgment still belong to human doctors and nurses — so AI’s more like an assistant than a substitute.
What’s the deal with AI and patient privacy?
With all that data, patient privacy is definitely a big concern.
Here’s how AI in healthcare keeps data safe:
- Data encryption: Think of it as a high-security lock on patient info.
- Anonymization: AI often strips away names and personal details to reduce risk.
- Compliance with strict laws: Regulations like HIPAA keep data protection on point.
Can AI make diagnosis more accurate?
Absolutely. AI is already proving itself with some serious accuracy points in healthcare. Here’s how:
- Enhanced imaging analysis: AI can detect subtle disease signs that even top specialists might miss.
- Predictive analytics: AI sifts through data to forecast potential health risks, letting doctors jump in earlier.
- Supporting radiologists: Acting as a second set of eyes, AI flags anything that might need a closer look.
Does AI help lower healthcare costs?
Yes, AI can seriously cut healthcare costs by making things run more efficiently.
Here’s it can do it:
- Better administrative processes: AI automates things like billing and scheduling so staff can skip the paperwork.
- Cutting down unnecessary tests: By improving diagnosis, AI helps doctors avoid repeat or ineffective tests.
- Speeding up drug discovery: AI accelerates research, saving money and time in developing new meds.
How good is AI at spotting rare diseases?
AI is making some big strides in spotting rare diseases — ones that can be tough to diagnose.
Here’s what it brings to the table:
- Pattern recognition: AI finds subtle clues that might point to rare diseases, even in routine data.
- Genetic testing analysis: Many rare diseases are genetic, and AI is excellent at combining genetic data to spot issues.
- Supporting specialists: AI tools flag anything unusual, helping doctors catch conditions that might otherwise go undiagnosed.
Can AI improve surgery outcomes?
AI is giving surgery a serious upgrade by adding a lot of precision and real-time guidance.
Here’s how it helps:
- Real-time feedback: AI provides insights during surgery, helping surgeons make incredibly accurate moves.
- Reducing human error: AI-guided tools help avoid mistakes, especially in high-stakes procedures.
- Making minimally invasive surgery easier: AI supports techniques that mean less pain and faster recovery for patients.
Summing up
So, it’s pretty much a given that AI is already having a tremendous effect on healthcare today.
From automating mundane tasks to assisting surgeons in the operating room, these AI in healthcare examples showcase the huge host of benefits that AI brings to the table.
If there’s one thing that’s for sure, it’s this: These advances will only keep accelerating in the coming years. Stay tuned because things are poised to get even more exciting!
