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AI & Medical Robotics: A Perfect Duo for Diagnosing Diseases

DEC 17, 2024

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Can a robot diagnose illness better than a doctor? In recent years, the gap between healthcare and robotics has rapidly narrowed, thanks to groundbreaking advances in AI and medical robotics. As per Grandview research, the market for medical robotic systems was valued at USD 25.56 billion in 2023 and is expected to expand at a compound annual growth rate (CAGR) of 16.55% between 2024 and 2030. The ageing population, in particular, is driving up demand for precise surgical operations due to the rising frequency of illnesses, including cancer, neurological problems, and orthopaedic ailments. AI in healthcare has played a massive role in enhancing the precision of surgical procedures to provide care in remote areas. Integrating AI and robotics in medical diagnosis makes healthcare more efficient, accurate, and, most importantly, patient-centered. In this blog, we’ll explore how AI and medical robotics work together as a powerful duo to diagnose diseases, tackle challenges, and move toward a future of robot-assisted diagnoses.

 

Medical Robotic Systems Market Size

 

Evolution of AI Technologies in Healthcare

 

Rule-Based Systems

Rule-based or expert systems represent an early form of artificial intelligence in healthcare. These systems rely on predefined rules and logic to emulate decision-making processes like human experts. Rule-based systems assisted in diagnosing diseases, recommending treatment protocols, and even guiding medical practitioners in clinical decision-making. They follow an "if-then" logic, where specific symptoms or test results lead to corresponding diagnoses or actions. However, they are not good at handling complex, dynamic, or ambiguous medical scenarios that require nuanced interpretation. 

Machine Learning Algorithms

Machine learning is utilized in predictive modelling, risk stratification, and medical imaging analysis applications. Healthcare systems trained on machine learning (ML) algorithms can learn patterns from data rather than rely on fixed rules.  These algorithms can process vast amounts of patient data—from electronic health records (EHRs) to lab results—and identify patterns humans might miss. For example, based on historical data, ML models can detect early signs of diseases like cancer or personalize treatment plans. Unlike rule-based systems, ML algorithms enhance their intelligence over time as they are subjected to more data.

Deep Learning Models

In healthcare, deep learning models are compelling for image recognition tasks, such as interpreting medical scans like X-rays, MRIs, and CT scans. Compared to human experts, these models can accurately detect anomalies such as tumours or fractures. Deep learning models in healthcare are also used for genomic analysis, drug discovery, and even personalized medicine, where they learn to tailor treatments based on individual patient characteristics. However, deep learning models in healthcare are data-hungry and require significant computational resources, and their "black-box" nature can make them challenging to interpret.

Natural Language Processing (NLP)

With medical records, clinical notes, research articles, and patient reports stored in accessible text format, NLP helps computers understand, interpret, and generate human language. In addition, it extracts relevant information from electronic health records (EHRs), identifies symptoms from patient narratives, and even summarises medical literature for research purposes. NLP is also used in chatbots and medical robots for patient monitoring interactions, voice-enabled assistants for physicians, and for assessing mental health through text analysis. Despite its promise, challenges remain in handling medical jargon, ambiguity, and complex language structures.

 

Exploring the spectrum of robots in healthcare

 

1) Modular robots

Modular robots consist of individual, self-contained units that can be reconfigured to form different structures or perform various tasks. Each module typically has sensors, actuators, and control systems, allowing them to work collaboratively or independently. The flexibility and adaptability of modular robots make them particularly useful in environments that require high versatility, such as search-and-rescue missions or industrial assembly. By connecting modules in different configurations, these robots can change shape and function to meet specific needs, offering a level of customization impossible with traditional fixed robots.

2) Mobile robots

Mobile robots are designed to move through their environment without external guidance, often using wheels, tracks, or legs. These robots have sensors (such as cameras, lidar, or ultrasonic sensors) and navigation systems to perceive their surroundings and navigate autonomously. Mobile robots are widely used in various applications, including warehouse automation, autonomous vehicles, and delivery systems. Their ability to move in dynamic environments makes them invaluable for tasks that require mobility and adaptability, like transporting goods or providing surveillance in large areas.

3) Surgical-assistance robots

Surgical-assistance robots are advanced robotic software systems designed to assist surgeons in performing medical procedures with precision and minimal invasiveness. These robots typically feature highly articulated robotic arms, specialized tools, and high-resolution cameras for enhanced visualization. One of the most well-known examples is the da Vinci Surgical System, which allows surgeons to control robotic arms remotely, offering excellent dexterity and control during complex surgeries. These robots help improve surgical outcomes by reducing human error, minimizing trauma to the patient, and enabling more precise operations, especially in delicate or hard-to-reach areas.

4) Social robots

Social robots are designed to interact with humans in a way that mimics human social behaviour. They are equipped with advanced sensors and artificial intelligence (AI) to recognize emotions, respond to verbal and non-verbal cues, and engage in meaningful conversations. These robots are used in various contexts, such as eldercare, therapy, and education, where human-robot interaction can enhance the user experience. Social robots can help cure loneliness, provide mental health support, or provide educational companionship. Their ability to adapt to social contexts makes them valuable tools for improving human well-being and supporting social integration.

5) Autonomous robots

Autonomous robots in healthcare can perform tasks without direct human intervention, relying on onboard sensors, AI, and machine learning algorithms to perceive and make decisions based on their environment. These robots can operate in dynamic and unstructured settings, making them ideal for autonomous vehicles, drones, and industrial automation applications. Through continuous learning and adaptation, autonomous robots can improve their performance over time, making them increasingly effective in complex environments. Their independence allows them to perform dangerous or repetitive tasks, reducing the need for human presence in hazardous areas. Check out this informative video on how AI is pushing healthcare robotics towards autonomy.

 

 

6) Service robots

Service robots are designed to assist humans by performing specific tasks in industries such as hospitality, healthcare, and domestic chores. These robots can range from vacuum cleaners and lawnmowers to robots used in hotels for concierge services or hospitals for delivering supplies. Service robots are equipped with sensors to navigate environments, interact with objects, and perform their tasks autonomously or semi-autonomously. Their main goal is to enhance efficiency and improve service quality, reducing labour costs and human workload while increasing reliability and productivity.

 

Role of robotics in healthcare

 

1) Elder Care

In elder care, robotics in medical diagnoses has shown immense promise in improving the quality of life for older adults, especially those with mobility limitations or cognitive impairments. Robots in elder care assist with daily activities such as medication reminders, meal delivery, and even companionship. They are meticulous, continuously monitor for dangers, and provide AI-driven treatment planning during emergencies. Social robots like PARO, a therapeutic robotic seal, provide emotional support and engagement to senior citizens. They reduce the feelings of loneliness and depression among seniors. 

2) Patient Monitoring

Medical robots for patient monitoring predict potential complications, suggest personalized treatments, and continuously and in real-time assess vital signs and conditions. Autonomous robotic systems use AI for disease diagnosis, tracking a patient's heart rate, blood pressure, temperature, and oxygen levels. They alert healthcare providers about abnormalities or deteriorating conditions. Robots can ensure constant vigilance by monitoring patients in remote or home settings without continuous human oversight.

3) Surgical Procedures

Robots in healthcare have enhanced the quality of precision and sped up recovery times.  AI robotics in surgery is particularly valuable in delicate operations, where precision is critical, and can significantly reduce the risk of infection. These systems use robotic arms controlled by the surgeon through a console that provides a high-definition 3D view of the surgical site. Due to its ability to reduce tissue damage, it's helpful in complex surgeries, such as prostatectomy, heart surgery, and orthopaedic procedures. 

 

 

4) Rehabilitation Therapies

Medical robotics can personalize rehabilitation therapies by providing special intensive care for patients recovering from injuries, strokes, or surgeries. Robotic exoskeletons and robotic-assisted devices are used in physical therapy to support and guide patients through rehabilitation exercises. Their repetitive and precise movements help patients in regaining mobility. They assist patients with walking or hand movements, progressively increasing the complexity of movements as patients improve. 

 

Applications of AI-driven healthcare robotics

 

1) Medical Imaging Analysis

AI-driven healthcare systems can accurately position imaging equipment for X-rays, MRIs, and CT scans with minimal errors. The precision is so sharp that subtle abnormalities can be detected accurately, which a human can easily miss. Mobile imaging robots are expanding access to diagnostic imaging by bringing high-quality equipment directly to patients, even in remote locations or at the bedside. In image-guided interventions, such as biopsies or surgeries, robots enhance the effectiveness of treatment by assisting in precise targeting.

2) Disease Diagnosis

AI-powered medical robots combine machine learning algorithms with real-time data analysis from various diagnostic tools, providing consistent, objective, and precise results. They analyze a patient's medical history, laboratory results, and genetic information to offer accurate and timely diagnoses. With early intervention, they have been able to detect early signs of diseases such as cancer, cardiovascular conditions, and neurological disorders.

3) Treatment Planning

Precision data analysis and predictive modelling provided by AI-driven robots can enhance personalized and AI-driven treatment planning. AI algorithms can help clinicians identify the most effective treatment plans for individual patients. In oncology, for instance, AI in healthcare can analyze tumour molecular profiles to suggest the most appropriate targeted therapies or immunotherapies, which increases the likelihood of successful treatment. 

4) Drug Discovery

The identification of potential drug candidates can be accelerated with AI-driven healthcare systems. They can verify how certain compounds might interact with biological targets and predict clinical trial effectiveness.  In the traditional drug development process, it can take years or even decades to bring a new drug to market. Still, AI models can study genomic data, chemical structures, and biological pathways—at a remarkable speed. They have already already contributed to the development of new therapies for diseases like cancer, Alzheimer's, and rare genetic disorders. 

5) Personalized Medicine

AI-powered medical robots can tailor medical prescriptions to each patient's characteristics, and robotic systems can be programmed to navigate the body with extraordinary accuracy. They administer treatments with greater precision, such as robotic surgery or targeted drug delivery systems. The patient’s response to the treatment can be monitored using real-time information, and therapies and dosages can be adjusted dynamically. 

 

Critical challenges for AI robotics in medical diagnosis

 

1) Cultural Acceptance

Integrating AI-driven robots into sensitive and personal spaces like the healthcare sector can discomfort patients and medical professionals. Many individuals may feel uneasy about being treated by machines when it comes to complex and intimate aspects of care, such as diagnosis and surgery. Concerns about autonomous robots in healthcare replacing human workers and fears about dehumanization or job loss can create scepticism. Cultural and ethical considerations around privacy, autonomy, and the purpose of technology in life-saving decisions complicate the acceptance of AI robotics.  

2) Data Protection and Security

AI and medical robotics depend on vast datasets to function effectively, and this data is often stored or transmitted across networks, raising the risk of cyberattacks, data breaches, and unauthorized access. Given the sensitive nature of medical information—from personal health records to genetic data—the potential for privacy violations is a serious concern. The odds of data manipulation or hacking grow as the data is exchanged in real time between machines, hospitals, and healthcare providers. The encryption protocols and cybersecurity measures must comply with healthcare regulations like HIPAA (Health Insurance Portability and Accountability Act) to reinforce patient trust in AI for disease diagnosis.

3) Lack of Human Empathy 

In healthcare, emotional support is needed for patients dealing with chronic illness, mental health issues, or end-of-life care. However, robots can’t replicate the empathy, understanding, and emotional connection that human caregivers provide. Regardless of technological sophistication, robots struggle to understand the nuances of human emotions, nonverbal cues, and subtle expressions of distress or comfort. Patients can feel isolated in their presence and perceive the robots as cold, impersonal machines.  

4) Complex UI

Most robots require specialized training for effective operation and troubleshooting. For instance, healthcare workers can only interface with robots if their control systems are intuitive and the robots' user interfaces are simple. Similarly, patients may find it challenging to trust or interact with a robot if it is not designed with ease of use in mind, especially those who are elderly or have limited technological literacy. Robots must be designed to emphasize simplicity, intuitive controls, and user-friendly interactions that accommodate varying levels of technical knowledge.  

5) Energy Supply 

Healthcare robots require a consistent and reliable energy supply to function, especially in environments where mobility and long operation times are necessary.  Battery life limitations and energy consumption can be problematic in mobile robots, such as those used for patient transport or surgery assistance. Frequent recharging or battery replacements disrupt the continuity of care and limit the robot's ability to perform tasks. In rural areas where power supply infrastructure may be less reliable, the functionality of AI-driven robots could be compromised.

 

5 Medical robots taking healthcare by storm

 

1) PARO Therapeutic Robot

Developed by Japan's National Institute of Advanced Industrial Science and Technology (AIST), the PARO Therapeutic Robot is designed to provide the benefits of animal therapy in settings where live animals may not be feasible. Modelled after a baby harp seal, PARO is equipped with advanced sensors that guide its system to move its head, limbs, and flippers, make realistic sounds, and exhibit behaviours that mimic a living animal.  It responds to touch, voice commands, and environmental cues and can learn from interactions.  For example, gentle stroking may prompt PARO to purr, while rough handling could lead to defensive reactions. PARO's technology includes tactile, auditory, light, temperature, and posture sensors, as well as AI that helps it recognize voices and adjust its behaviour.   

2) The TUG

Aethon developed the TUG robot, a highly advanced and intelligent mobile robot designed to optimize hospital logistics. The TUG robot uses various sensors, including ultrasonic, infrared, and lidar, to detect and avoid obstacles in real-time. Utilizing simultaneous localization and mapping (SLAM) technology, it creates and continuously updates hallways, elevators, and patient room maps. This technology allows the TUG robot to take on various critical tasks, from delivering medications on-demand or per a preset schedule to transporting linens, supplies, and medical waste, freeing staff to focus more on patient care. The robots can carry a range of payloads, from small vials to extensive linens, with secure lockable compartments for sensitive items. 

3) Xenex Germ-Zapping Robot

The Xenex Germ-Zapping Robot is a disinfecting system that uses pulsed xenon ultraviolet (UV) light to eliminate harmful pathogens. Unlike traditional mercury-based UV systems, Xenex employs brief, intense bursts of UV-C light, which are highly effective at damaging microorganisms' DNA and RNA. This technology is potent and safer for the environment, as it avoids the toxic risks associated with mercury. Its 356-degree coverage makes it easier to reach disinfected surfaces that are not easy to get, while integrated motion sensors stop the UV emission if movement is detected. Its portable, compact build allows it to be easily deployed throughout healthcare facilities. The Xenex robot is especially effective against formidable pathogens like MRSA, C. difficile, and SARS-CoV-2.  

4) Da Vinci Surgical Robot

Since its FDA clearance in 2000, The da Vinci Surgical System has been used in over 775,000 procedures worldwide across various specialities like urology, gynaecology, cardiac, and general surgery. It consists of a surgeon’s console, a patient cart with robotic arms, and advanced vision and instrument systems, allowing surgeons to perform surgeries with 1-2 cm incisions rather than the larger cuts typical of traditional surgery. The system reduces the physical strain on the surgeon by enhancing surgical dexterity. The recent addition of the Da Vinci 5 systems has brought even more advancements, like AI feedback and "force feedback" technology, which enhances surgeon autonomy and provides a better understanding of tissue tension.

5) CyberKnife

CyberKnife is a non-invasive cancer treatment system that utilizes advanced robotics and precision radiation to target tumours while minimizing damage to surrounding healthy tissue. Unlike traditional surgery, which can be invasive and require long recovery times, CyberKnife uses stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) to deliver high doses of radiation in fewer sessions. One of its main features is a robotic arm for flexible tumour access, a linear accelerator (LINAC) for high-energy X-rays, and an advanced image guidance system that continuously tracks the tumour’s position, even accounting for movements like breathing. CyberKnife’s ability to precisely deliver targeted radiation allows for treatments with fewer side effects and faster recovery times. 

 

What’s the future like for AI and medical robotics in healthcare?

 

Integrating AI and medical robotics is already making waves, with industry giants like Google diving into healthcare. Google, for example, is working with healthcare providers to create predictive models that can anticipate health issues before they become serious problems. 

Beyond diagnostics, AI in healthcare also improves patient care by facilitating preventive measures and more precise treatments. Brain-computer interfaces (BCI) allow doctors to better understand neurological conditions by "reading" brainwaves and even controlling robotic limbs, offering new hope for patients with severe mobility impairments.

Wearable health technology is another exciting development. Devices like fitness trackers and smartwatches are not just for counting steps—they’re becoming critical tools in early diagnosis. One striking example is an Indian dentist who discovered he had a 99% blockage in his arteries after performing an ECG using his smartwatch and ended up saving his life. These devices can monitor heart rate, track movement disorders (such as Parkinson’s disease), and even send distress signals if something goes wrong.

AI-driven robots also promise to expand healthcare access, particularly in underserved regions. Through telemedicine, patients in remote areas can consult with doctors miles away and receive real-time medical advice and treatment. The technology isn't just limited to consultations—it’s also used to educate patients about disease prevention and manage conditions without the need for frequent in-person visits. The future of healthcare is here, and it's powered by AI and medical robotics.

 

Get an AI-integrated robot for precise treatment & diagnoses

 

Successful healthcare organizations will adapt these technologies to overhaul their workflows and create more intelligent, efficient systems as we progress. While we’re still in the early stages of exploring AI's full potential in healthcare, there’s no denying that the journey has already begun, and the results will be jaw-dropping. It may take time to realize AI’s capabilities fully, but the result promises a healthcare system that is smarter, more efficient, and ultimately more accessible.

As one of the best next-gen AI/ML solutions provider companies, Webelight Solutions Pvt. Ltd. knows your needs for improving precision, diagnosing, and creating more personalized treatment plans. Whether you need assistance developing intelligent systems for disease diagnosis, enhancing medical imaging with AI-powered analysis, or optimizing AI robotics in surgery assistance, we provide innovative AI/ML solutions for healthcare that can be life-changing for your patients. With a focus on automation, predictive analytics, and patient-centered care, we can help healthcare organizations create a brighter, more efficient future. 

 

Don’t let human error stand in the way. Connect with our AI/ML development team and get the robotic precision your patients deserve!

 

FAQ's

AI and robotics have made remarkable strides in healthcare, offering impressive capabilities in diagnosing diseases. While they can't completely replace human doctors, AI-powered systems can analyze large amounts of data, including medical images and patient records, to identify patterns that might be missed by a human. These technologies enhance doctors' abilities to make precise diagnoses and recommend treatment plans, improving patient outcomes.