How AI Is Reshaping Healthcare: From Diagnostics to Digital Twins
There was a time when people encountered serious health issues after age 50 or 60. However, the unhealthy and hustling lifestyle has impacted the current generation, and now the health issues arise around 30 or earlier. Sometimes, a lack of nutrition or diet exhaustion acts as a poison, damaging the body slowly.
Now imagine if your doctor can detect the symptoms before the diagnosis and tests recommended. These health hints may save you from unexpected mishaps or emergencies.
Beyond AI based diagnostic tools, wearables, and remote checkups/operations, digital twins in the healthcare industry are raising the bar of innovation.
This blog explores the relevance of digital twins, including their real-world benefits, challenges, and future impact.
Relatable Real Life Aspect: Digital Twins in Healthcare
You may have noticed that people are struggling with cardiac attacks, tumours, and liver cancer more frequently than ever.
No matter how health-conscious they are, they still struggle with serious health issues. Headlines and new stories of sudden health issues have become a daily inshots.
Yes, doctors recommend having a routine checkup to confirm that everything is okay. But some people don’t prioritise it; they think it's a waste of time and money.
They have a misconception in their mind, if you visit a doctor, they will definitely recommend tests and take medicines. After such tests and medicine, you realize that something is disturbing your health, and then you start taking medicine.
Our body shows early signs/ signals that we often neglect to address, sometimes confusion.
However, what if you predict the mishaps before you reach the critical stage?
Digital twins turn this into reality predicting the health complications before.
In 2024, the digital twins market was valued at $ 2094.73M. By 2032, the market for creating digital twins in the healthcare market will surge to $15,211.73M at a CAGR of 28.17%.
Its growth is visible in the Asia Pacific region, and North America has the largest market share in digital twins.
Do you know what's driving the rapid growth of the digital twins market?
Let’s understand the need for digital twins in brief with bullet points.
It saves time wasted on frequent visits and associated expenses.
Each person's body reacts differently, thus there is a need for personalized medicines.
It’s better to predict in advance with utmost accuracy, blending the potential of AI, IoT, Big Data, and other emerging technologies.
After the pandemic, patients became accustomed to remote access for everything, including health care support, on-demand online monitoring, and prediction.
It enables rapid research and development for the detection of upcoming drug and treatment launches.
Beyond just experiment or trend it is the essential vital aspect dominating healthcare.
What are Digital Twins in the Healthcare Industry?
Digital Twins are a trending innovation in healthcare empowered by AI. It transforms the process of diagnosis and cures critical diseases. It can detect and predict the patient's physiological systems, organs, and complications of health earlier than it's too late to treat.
Nowadays, everyone wears wearable devices to keep an eye on everything from heart rate to oxygen level to blood sugar and get alerts, but what if they miss due to charging issues or other reasons?
These wearables capture the patient's health data, but they may not provide more information than a professional.
Beyond offering precision and accuracy, it manages the AI and data-driven personalized hospital ecosystem with virtual representation.
It replicates human health conditions, leveraging artificial intelligence in healthcare, continuously receiving data and evolving.
When Digital Twins are Derived and their Evolution and Keytypes
Initially, the context came to light in the early 2000s, and got traction when NASA also incorporated it into its Apollo missions. Later, it was implemented across different domains, including automotive, manufacturing, and aerospace, and is now driving transformation in the healthcare industry.
In the mid-2010s, digital twins were used to simulate models before performing operations, including organ transplantation, and clinical trails.
Beyond just personalized medicine, it has embraced medical device innovation by 2025.
Based on our review of various research insights, 70% of the cooperation will take the initiative to develop digital twins by the end of 2025.
How do Different Types of Digital Twins React in Healthcare?
From digital representation to engineering visualization, digital twins have enabled a range of key digital twin technologies. The convergence includes the following things for the proper functioning of Digital twins.
Data Collection: Capturing and feeding human body temperature data, blood pressure, movement, wear, or lab data, and other measurable parameters, integrating sensors to physical assets like wearables.
Data Integration: We have just collected data, which needs to be refined before transmission, typically handled by IoT platforms or by setting up cloud infrastructure.
What Can We Do with Digital Twins?
It enables the AI-powered Model and Replication, capable of replicating the virtual model across different organs and discovering solutions to medical issues through adaptive and default learning. While simulation is not automated to work with real scenarios, it chooses hypothetical scenarios.
Key Types of Digital Twins
Component Digital Twins:
Replicating the prosthetic joint, pacemaker, and stent designs in an arterial environment is one of the real-life examples that predict outcomes. It is a basic component-type digital twin, yet it is worth it to avoid physical damage.
Asset Digital Twins:
Next are asset digital Twins, which are a heart replica. As we know, the heart contains valves, electric systems, and all chambers.
Siemens Healthineers has replicated the heart to slow the progression of cardiovascular disease, and has suggested new ways to treat it in collaboration with Mayo Clinic.
System Digital Twins:
Till now, digital replication was implemented for a few parts or multi-component assets, but now with system twins, it is possible to uncover insights for ICU operations. It fits in scenarios that are hard to detect and have a high risk of many infections, like COVID-19.
Process Digital Twins:
Before operating on human bodies, these digital Twins can be used to understand the impact on the human body. In hypertension cases, digital twins can tackle insulin resistance and inflammation, and limit medication usage.
Digital Twins Advantages that You Must Know
Until then, whatever we mentioned in the above section is about what digital twins are and how they are evident in the real world. Now, we move to the section that highlights the advantages of Digital Twins beyond conventional modeling.
Personalized Treatment Plans
Before the actual surgical procedure, personalised healthcare strategies can be developed on these virtual models to provide patients with the best treatment.
Risk-free Medical Experimentation
It’s common yet risky for MRI machines, blood pressure machines, or CT scanners to stop functioning. Thus, these replicas can proactively inform and provide needful maintenance assistance.
Predictive Maintenance for Medical Devices
In hospitals, for patients to recover correctly, a safe, clean, and hygienic environment is essential. Thus, the digital twins optimize and enable proper operational mechanisms and asset allocation to the patient, prioritizing the schedule.
Real time Monitoring
With the union of genAI, IoT, ML, and wearables, it is easier to feed real-time data into these integrated digital twin platforms. That helps to speed the recovery of patients diagnosed with diabetes and cardiovascular disease.
Improved Clinical Trials & Drug Discovery
Digital twins can be implemented at a large scale and within a single organization. It assists healthcare experts in strategic planning and in testing policies, vaccines, and treatment procedures before full enforcement.
Optimize Hospital Operations
No more assumptions, just impactful treatment through pre evaluated outcomes and reactions of clinical trials.
Digital Twins Challenges that Impact
Digital Twin showcases the future outlook of the healthcare industry. Yet some restraining keypoints need to be addressed.
Of course, for the proper functioning of the digital twins, computational power, a secure infrastructure, and AI models are required. So hospitals and research centers must have trained professionals.
Health data is sensitive, and when it comes to large-scale data, it is unlikely to avoid breaches and to protect patient privacy.
Implementing the AI-powered integration into existing healthcare systems running older versions is way more complex than we imagine.
Progressive Move: Unlocking Personalized Care by Creating Digital Twins in Healthcare
Beyond experiments on models, it is emerging as a mainstream clinical tool, transforming the approach to treating patients and helping restrict the spread of diseases before they take lives.
Personalization is evident across every industry, and the healthcare industry also has tools, but Digital Twins is an extraordinary innovation. This enables real-time inspection, predictive diagnosis, and patient-specific therapies.
Furthermore, it will optimize the utilities/ facilities for patients and allow testing the best possible methods and practices to cure diseases before implementing them in humans.
Be it creating tissues, lungs, hands, brain, heart, or the entire body, physicians can predict unexpected responses to surgical treatments. For clinical trials, drug discovery, and reactions, we will optimize manufacturing costs and accelerate launch at the right time.
Yes, challenges exist that can be resolved by strengthening the data security measures, and will shift the burden of delayed treatments with patient consent.
Government, tech drivers, and healthcare experts are interested in optimizing the efficiency and effectiveness of medical treatments through these Digital twins.
Final Words
Digital Twins are replicas of human organs that act as key enablers, enabling precise prediction, prevention, and progress tracking at every step. It's a promising innovation evident in the healthcare industry that influences every domain. Investors provide fuel, IT drivers optimize workflows, and healthcare experts collaborate to make it a successful, proactive, patient-centric paradigm.
Now, things are no longer limited to a reactive model; this will enable us to make decisions prioritising ethical considerations, medical regulations, and compliance.
At Eternalight Infotech, we ensure that all our pilot projects and healthcare apps leverage the latest sensor, data, and integration technologies we implement, which comply with FDA and other health department regulations. Thus, it can predict real-time information and value-added deliverables.
Ayushi Shrivastava
(Author)
Senior Content Writer
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