AI in Healthcare: The Promise of Automated Medicine
Faster, more accurate, and only at a fraction of the cost, Artificial Intelligence is key to a fully automated future in medicine. Envision a world where an AI-powered device detects cancer at its earliest stage or predicts a heart attack even before it happens. In healthcare, every second counts, and AI offers the speed, precision, and cost-efficiency necessary to redefine modern medicine. By enabling automated systems that deliver timely diagnoses and personalized care, AI is emerging as a cornerstone of innovation in the medical field.
Healthcare systems worldwide face mounting challenges in achieving the “quadruple aim”: enhancing population health, improving patient experiences, supporting caregiver well-being, and reducing escalating costs. As these pressures grow, the need for smart, automated solutions has never been more urgent. AI, with its ability to process vast datasets and deliver actionable insights, is uniquely positioned to address these demands, optimizing care delivery while alleviating the burden on caregivers.
This article delves into the important role of AI in reshaping healthcare. It explores the respective roles of Cloud and Edge AI in enabling automation and concludes with how ModelNova is empowering engineers with advanced Edge AI development solutions to meet the growing demand for smarter, more adaptive healthcare solutions.
The Impact of AI in Healthcare: A Revolution Underway
While Advertising and Media, BFSI (Banking, Financial Services, and Insurance), and Healthcare currently account for the top 3 largest revenue shares in the global AI market, the healthcare sector is projected to take the lead by 2030.
The Fortune Business Insights report highlights a remarkable trajectory for the global AI in healthcare market. Valued at USD 19.54 billion in 2023, the market is projected to surge to USD 490.96 billion by 2032. This equates to a staggering annual growth rate of 46.06%, with the market expanding by an impressive 2,412% over the nine-year period.
The reason being that the sector spans use cases such as robot-assisted surgery, dosage error reduction, virtual nursing assistants, clinical trial participant identification, hospital workflow management, preliminary diagnosis, wearable health tech, and automated image analysis.
Key Use Cases in Healthcare
1. Robotic Surgery
Robotic surgery is redefining precision and efficiency in modern medicine, offering unmatched accuracy and repeatable outcomes that support surgeons and improve patient care. Contrary to common misconceptions, most robotic surgical systems do not operate autonomously. Instead, they are guided by skilled, certified surgeons who leverage this advanced technology to enhance procedural outcomes.
The journey began in 2000 with Intuitive’s da Vinci Surgical System, the first robotic surgery platform to gain FDA clearance for general laparoscopic procedures. This system revolutionized minimally invasive surgery, enabling unprecedented precision and accuracy across numerous procedures. With over 1,700 units installed globally and more than 775,000 procedures performed, da Vinci has become the gold standard in robotic-assisted surgery, accounting for nearly 75% of prostate cancer operations in the United States.
Intuitive’s Ion system, FDA-cleared in 2019, showcases another milestone. Designed for minimally invasive lung biopsies, the robotic catheter navigates through intricate airways, allowing physicians to access deep lung areas with remarkable ease. Similarly, the NAVIO Surgical System simplifies total knee replacements by utilizing real-time bone mapping and 3D modeling to guide surgeons during operations. FDA-cleared in 2018, this system minimizes the need for preoperative scans, offering a tailored approach to joint replacement surgery.
2. Predictive Analytics
Predictive analytics, a cutting-edge business intelligence capability that AI brings to the table, leverages machine learning, statistics, and historical data to forecast future outcomes. In healthcare, its impact is groundbreaking, offering professionals the ability to anticipate and address patient needs with unparalleled accuracy.
For instance, healthcare providers use predictive analytics to flag patients at high risk of readmission within 30 days. This foresight allows tailored follow-up care, improving recovery rates and reducing hospital costs. By analyzing vitals, predictive models identify potential complications before they escalate, enabling rapid interventions.
Electronic health record systems can reveal predictive health data about patients most likely to no-show. Studies from Duke University illustrate its potential: “predictive modeling of electronic health records identified an additional 5,000 potential no-show patients annually, enabling proactive measures like appointment reminders or transportation support.”
Innovators like Anthem are taking it further, crafting personalized healthcare protocols through behavioral pattern analysis. These insights optimize care delivery and enhance patient engagement, ensuring individuals adhere to financial and clinical responsibilities. Predictive analytics not only drives efficiency but also empowers healthcare providers to deliver tailored interventions, improving outcomes and operational effectiveness.
3. Diagnosis
Early and accurate diagnosis is the foundation of effective treatment, dramatically improving survival rates for many diseases. For instance, early detection of breast cancer yields a five-year survival rate exceeding 90%, compared to significantly lower outcomes when diagnosed in later stages. Advances in AI-driven diagnostics are revolutionizing healthcare, making timely detection increasingly possible and available.
Omdena’s AI-powered app in Liberia exemplifies this progress, predicting malaria outbreaks and identifying high-risk areas. This tool allows health officials to preemptively target interventions, protecting vulnerable populations like children and pregnant women. Similarly, AI is transforming oncology by facilitating personalized cancer treatments through genomic analysis. By identifying genetic mutations, AI enables tailored therapies that boost efficacy, minimize side effects, and expedite drug discovery.
In cardiology, AI analyzes electrocardiograms, imaging, and patient data to predict cardiovascular diseases with impressive accuracy—up to 93% in some studies. These non-invasive diagnostic tools save lives by detecting risks early, offering a glimpse into a future where AI seamlessly integrates with healthcare to enhance outcomes across disciplines.
AI-Powered Medical Equipment and Devices
The convergence of AI and medical technology is shaking-up healthcare delivery, pushing the boundaries of diagnostics, treatment, and patient care.
AI-powered medical equipment are no longer just futuristic concepts; they are actively reshaping how healthcare providers and patients interact with technology. These equipment, powered by either/both cloud-based AI and/or edge AI architectures, cater to a variety of needs, from streamlining workflows in radiology to providing real-time insights for emergency interventions.
Cloud-Based AI Paired With Medical Equipment
Cloud AI platforms provide centralized processing power and vast data storage capabilities, offering healthcare professionals tools that analyze complex datasets and generate actionable insights. Some examples include:
Aidoc
This radiology-focused platform rapidly analyzes medical images, identifying critical conditions such as brain bleeds and pulmonary embolisms. By prioritizing urgent cases, Aidoc helps radiologists optimize workflows, saving valuable time.
HeartFlow Analysis
By uploading coronary CT scans to a secure cloud, this tool generates 3D models to evaluate blockages in arteries and help cardiologists determine non-invasive treatment strategies. Its cloud-based infrastructure enables seamless collaboration and real-time decision-making.
Qure.ai
Specializing in democratizing healthcare access, Qure.ai leverages cloud computing to deploy AI solutions globally, detecting conditions like tuberculosis and head injuries, even in resource-limited settings.
Viz.ai
Designed for stroke care, this platform uses cloud-based AI to analyze CT scans for large vessel occlusions. It facilitates real-time collaboration between emergency responders and neurologists for faster interventions.
PathAI
This diagnostic tool employs machine learning to analyze pathology slides, improving cancer detection accuracy and aiding in the classification of cancer subtypes for tailored treatment plans.
Edge AI-Powered Medical Devices
Edge AI devices bring intelligence directly to the point of care, enabling real-time processing without relying on external data centers. Some real life examples include:
Butterfly iQ+
This portable ultrasound device integrates edge AI to analyze images in real-time, offering rapid diagnostics at the point of care without relying on external data centers. It’s widely used in remote and emergency settings.
iRhythm Zio XT
A wearable cardiac monitor, the Zio XT employs edge computing to record and analyze heart activity continuously, offering clinicians actionable insights without requiring constant cloud connectivity.
Medtronic Guardian Connect
Designed for diabetes management, this continuous glucose monitoring (CGM) system utilizes on-device AI to predict glucose trends and provide alerts to users and caregivers, ensuring better glycemic control.
Think Surgical’s TSolution One
A robotic system for joint replacement surgeries, this edge AI device (robodoc) performs precise bone cutting based on preloaded surgical plans, reducing dependency on external computational resources while enhancing outcomes.
The Persona IQ Smart Knee is a groundbreaking innovation in joint replacement technology, seamlessly blending Edge AI and Cloud AI to enhance post-surgery care. Implanted during knee replacement surgery, the device uses Edge AI to collect real-time data, such as range of motion, step count, and walking speed. This on-device processing ensures immediate data collection without depending on external networks.
The gathered information is then wirelessly transmitted to a home-based station and uploaded to a secure, HIPAA-compliant cloud platform. Here, Cloud AI processes the data, delivering detailed insights to healthcare providers. This hybrid approach allows for continuous, remote monitoring of recovery progress, reducing the need for frequent in-person visits and enabling quicker, more informed medical interventions when necessary.
By combining the immediate capabilities of Edge AI with the analytical power of Cloud AI, the Persona IQ Smart Knee sets a new standard in post-operative care, providing patients and healthcare providers with the tools to achieve better outcomes with less effort.
The adoption of AI in medical equipment is more than a technological milestone—it represents a paradigm shift in healthcare delivery. By combining the expansive capabilities of cloud computing with the localized intelligence of edge AI, these medical devices and equipment not only enhance operational efficiency but also empower personalized, data-driven care.
A Silent Innovator: embedUR and ModelNova
Driving innovation in this space, embedUR’s ModelNova (a modelzoo) is simplifying AI integration for low-power edge devices. By offering the developer community pre-trained AI models, blueprints and datasets, ModelNova enables businesses to accelerate their proof-of-concept phases, ensuring that cutting-edge AI solutions are accessible to engineers and enterprises alike.
Why there is no turning back from AI
Improving Efficiency and Accuracy
AI is already reshaping the practice and economy of the healthcare industry by streamlining workflows, reducing diagnostic errors, and enabling professionals to focus more on patient care. In fact, 92% of healthcare leaders believe that automation can address staff shortages by reducing repetitive tasks.
For example, AI-assisted surgeries have shown to cut hospital stays by over 20%, contributing to potential annual savings of $40 billion. Similarly, in diagnostics, AI excels by detecting diseases like cancer with up to 17% greater accuracy than human practitioners, offering faster, more reliable results for patients.
Driving Cost Efficiency
Automation powered by AI is poised to save the healthcare industry billions of dollars. By automating routine tasks such as data entry and lab testing, healthcare providers could reduce operational costs by an estimated $13 billion by 2025.
Technologies like AI chatbots, projected to save $3.6 billion globally in the same timeframe, further enable healthcare organizations to redirect resources towards patient care and cutting-edge medical innovations.
Enhancing Patient Outcomes
AI personalizes healthcare by analyzing individual patient data to develop tailored treatment plans. For instance, it identifies optimal drug therapies for complex conditions, using genetic profiles to maximize recovery rates. AI-powered diagnostic tools also detect subtle patterns and anomalies often missed by the human eye, ensuring more accurate and timely diagnoses that lead to better patient outcomes.
Expanding Global Healthcare Access
AI is expanding access to quality healthcare, especially in underserved regions. Wearable AI devices, for instance, monitor vital signs in real time, enabling remote patient management even in areas with limited infrastructure. This innovation minimizes the need for in-person visits while ensuring timely intervention, bringing life-saving care to previously unreachable populations.
Empowering Healthcare Through ModelNova and embedUR
embedUR’s ModelNova stands at the forefront of scalable Edge AI solutions, offering pre-trained models designed for rapid proof-of-concept development in healthcare settings and for other industries. By facilitating seamless integration of AI technologies, ModelNova equips healthcare organizations with tools to unlock AI’s full potential in addressing critical challenges, without needing to develop AI models or integrate them with the intended hardware on their own.
Healthcare Leads, But the AI Revolution is Just Getting Started
Healthcare may be one of the “big three” industries driving AI innovation, revolutionizing diagnostics, patient care, and operational workflows. But let’s not forget the ripple effect across other sectors. Agriculture is harnessing AI to optimize crop yields and manage resources sustainably. Media and advertising are being redefined with hyper-personalized campaigns and real-time audience insights. And these are just a glimpse of what’s unfolding.
Just because healthcare is leading doesn’t mean it’s the only frontier. Businesses in every sector can benefit from the precision, efficiency, and innovation AI offers. Curious about how Edge AI is revolutionizing industries like yours? Check out how healthcare and other industries are leveraging cutting-edge AI solutions in this video. Explore what’s possible when technology meets creativity, and start building the future today. If you enjoyed this piece, catch another interesting read on how IoT is also reshaping Healthcare.
