INTRODUCTION:

Medical technology is the use of technology in the healthcare or medical fields. The healthcare industry has benefited greatly from the introduction of new technology in recent decades. To ensure that we can address every health care issue that we currently face, medical technology has a significant role to play in the future¹. The medical field, which includes pharmacists, doctors, and nurses, is an extremely labour-intensive one. New medical technology, on the other hand, are what enable practitioners to advance in their careers, save more lives, and combat emerging illnesses.² This essay will first examine the state of global healthcare in the last ten years and how it has evolved, before going over seven exciting new developments in the field. The "application of organised knowledge and skills in the form of devices, diagnosis, medicines, vaccines, procedures, and systems developed to solve a health problem and improve people's quality of life" is how the World Health Organisation defines health technology. "The healthcare industry has undergone a significant transformation thanks to a range of cutting-edge new technologies, including genome sequencing, drone technology, electronic medical records, telemedicine, home-based care replacing hospital-based care, digital tools, and artificial intelligence (AI). Millions of individuals and patients are being assisted by health-tech firms and entrepreneurs that are bringing innovation and future technology into the present⁴.

Virtual Reality in Medical Sector:

By wearing a VR headset, users can virtually replicate an engaging event or experience in an interactive, computer-generated environment thanks to technology known as virtual reality (VR). Wearing specialised 3-D goggles with a glass screen or gloves that provide sensory input may be required to fully immerse oneself in the simulation and aid in learning.

Virtual reality finds application in patient care, medical marketing, diagnostics, teaching the public about diseases and medical conditions, and training future physicians as well as students. By 2025, the VR market is predicted to reach a value of over ~$5 billion globally¹⁹.

Biobank:

Biobanks are sizable collections of biospecimens linked to acceptable and qualifying personal and health data, such as genetic, family history, and medical records. Their primary purpose is to be used in health and medical research. Biobanks are legally recognized organizations that oversee the procurement and storage of biological material as well as some or all of the accompanying data and information gathering, testing, preservation, and distribution processes. A source of germline DNA, often extracted from buccal cells or peripheral blood, must be collected for genetics research. A biobank is an organized collection of biological specimens and participant health data. For reliable phenotyping and exposure assessment, health information at the time of specimen collection, including medical, treatment, lifestyle data, should be employed. They could concentrate on a particular kind of tissue or contain biospecimens from several origins that are pertinent to an illness like cancer.²⁰

Drone Technology:

Use of a drone or unmanned aerial vehicle (UAV) to transport medicine, supplies, and other medical equipment to patients receiving home care as opposed to a hospital. Patients who are in remote locations, such as an island, a rural community, or a forest, can receive medicine via drones and receive emergency medical attention. Drone use for virtual and telehealth care is one of the most beneficial uses. Businesses like Amazon, Walmart, and 7-Eleven have already begun using drones extensively to supply pharmaceuticals to consumers, pharmacists, and wholesalers. In a similar vein, drones have been deployed in the struggle against HIV, a longstanding threat to developing countries like the United States. Drones were utilised by UNICEF to deliver HIV testing kits to Malawi, an African nation with one of the highest rates of HIV infection globally³.The first official drone delivery in the US took place recently when the National Aeronautics and Space Administration (NASA) tested a drone carrying medical supplies to a small clinic in rural Virginia. Among the supplies were medications for asthma, high blood pressure, and diabetes.

Telemedicine:

The rapidly expanding discipline of telemedicine, which involves treating patients remotely using telecommunications technology, is one of the most potential applications for drones. Telecommunications is a crucial term in the definition of telemedicine. Sadly, commercial networks are unable to supply the connectivity required for telemedicine missions to remote, war-torn, or disaster-relief areas. The senior author (JCR) brought up the concept of utilising drones to build Instant Telecommunication Infrastructure (ITI) at the Yale/NASA Commercial Space Centre Telemedicine Program in 1998 when he was in Athens, Greece.

Medical Transport:

Because of their rapid response times and ability to traverse otherwise impassable terrain, drones are an attractive platform for providing medical treatment. In order to speed up the transmission of microbiological samples for HIV testing from remote clinics to NHLS centres, researchers from Denel Dynamics (UAV division) and the National Health Laboratory Service (NHLS) tested a proof-of-concept unmanned system in 2007. Médecins Sans Frontières (MSF) evaluated a drone-based approach to transport lab samples to hospitals for tuberculosis testing in 2014. This experiment demonstrated that drones could deliver viable laboratory samples in 25% less time than it would have taken to transfer them by land. According to a Salt Lake City, Utah, computer-based simulation study, 96% of the nation’s population can be reached by strategically positioned drones in less than a minute.

Nano Technology:

The need for novel pharmaceuticals and medical treatments has grown due to the expanding human population, the discovery of new diseases, and the emergence of pandemics. The development of nanotechnology offers a platform for new non-invasive in vivo diagnostic and therapeutic disease detection and treatment methods. Scientists have developed a Nano micelle that can be used to transport drugs to patients effectively and treat a variety of diseases, such as lung, colon, and breast cancer.⁶

The Lexicon of Nanotechnology:

It would be beneficial for us to become familiar with the language around nanotechnology before describing the potential applications of this technology in the healthcare field. Quantum dots, often known as nanoparticles. We are all aware that the surface area to volume ratio increases with material size. This guarantees the production of quantum effects and unique optical, physical, and chemical properties in nanoparticles. Nano tubes are tubes composed primarily of carbon that have walls that are one atom thick and resemble tubes.²²

Internet of Medical Things:

The Internet of Things, or IoT, is crucial to the healthcare sector. The term "Internet of Medical Things" (IoMT) refers to the way that medical objects can now be connected in order to monitor biological signals and diagnose patient conditions without the need for human intervention.A new era of digitalisation is upon us, one marked by wearables, smart industries and homes, and smart sensors in transportation. The Internet of Medical Things (IoMT) is the network infrastructure, software, services, and medical equipment that are connected to telemedicine and healthcare platforms. Smart sensors built into implanted or wearable smart devices that are networked via a body sensor network (BSN) or wireless sensor network (WSN) will first collect medical data from the patient's body. This information will be gathered online and utilised in the section that follows, which addresses the stage of prediction and analysis. Once the medical data is received, analysis can be performed by applying the appropriate AI-Based technique to convert and analyse the data. The primary function of the data acquisition sublayer, which is employed by a number of medical perception devices, is perception from the gathered data²³.

Benefits of the Iomt:

3 D Bioprinting:

3D bioprinting is a manufacturing technique that prints living cells with bionics to create layers of structures that resemble the architecture of natural tissues. Bioinks, or bioprinting materials, are derived from synthetic or natural biomaterials that can be combined with living cells. The apparatus and bioprinter constructs that the researchers employed to investigate human body functions in vitro. In vitro research conducted in two dimensions are not as meaningful as three-dimensional bioprinter constructs. The majority of 3D bioprinting's biological applications are found in the domains of materials science, bioengineering, and tissue engineering. pharmaceutical medication research and drug validation are using the technology more and more. At the forefront of bioprinting research are clinical situations such as 3D printed skin and bone grafts, implants, and even whole 3D printed organs⁸.

Benefits of Bioprinting in 3D:

1. Permits simulating the intended tissue or organ's actual structure. potential to completely transform medical treatment options in the future.

2. Potential development of medication treatments tailored to individual patients and organs that can be more precisely and successfully assessed.

3. Compatible with human tissues and cells biocompatible.

4. Having the intricate processes automated.

5. A reduction in human error occurs in that it's challenging to sustain the cell environment. Another obstacle is ethical issues.

6. There is a rise in energy usage.

Medical Coding;

The process of translating diagnoses, therapies, apparatus, and other medical services and supplies into universal medical alphanumeric codes is known as medical coding. Diagnoses and procedure codes are found in the medical record documentation, which also includes transcriptions of doctor's notes, test results, and radiologic pictures²⁵.

Need Of Medical Coding:

The documentation of our decisions, actions, and lessons learnt is the foundation of the healthcare income stream. The diagnosis, test results, and course of therapy for a patient might be recorded for insurance purposes, as well as to ensure high-quality care and patient compliance during subsequent visits. Hospitals and payers can communicate easily and consistently because to this standard language, which is required by the Health Information Portability and Accountability Act. All personal health data is stored digitally and is protected by codesform²⁶.There are six official HIPAA mandate code sets in the US that serve various purposes based on demands. Medical technology uses modifiers, National medication code, MS DRG, APC, HCPSC, ICD-10-PCS, and ICD-10-CM.

AI in medical Technology and Healthcare:

"Artificial intelligence" (AI) in the context of healthcare refers to the application of computer software and machine learning to simulate human intellect when it comes to the analysis, documentation, and comprehension of complex medical and health care data. Artificial intelligence (AI) refers to computer algorithms' ability to approximate conclusions based on available facts. Algorithms for artificial intelligence (AI) are employed in a wide range of industries, such as medication research, therapy, personalised medicine, diagnosis, and patient and care monitoring. AI technology differs from earlier technologies in the healthcare sector in that it can collect data, process it, and deliver a better outcome for the user. More developing nations than ever before now have access to computers and the internet thanks to a number of innovative tech companies like SpaceX and the Raspberry Pi Foundation. Artificial intelligence (AI) is a quickly evolving computer technology that is starting to be applied extensively in the medical industry to enhance professional standards and efficiency of clinical practice while averting medical errors. The study of imaging scans, such as CT or MRI scans, is one possible use of AI in radiology.

Application of AI in medical technology¹²:

Cardiovascular:

Artificial intelligence algorithms have shown encouraging results in correctly diagnosing and risk stratifying patients with concern for coronary artery disease, suggesting potential as an initial triage tool, even though few studies have directly compared the accuracy of machine learning models to clinician diagnostic ability. Various techniques have been used to predict patient death, drug side effects, and adverse events following therapy for acute coronary syndrome. Additionally, wearables, smartphones, smart watches, bands, and internet-based technologies show that they can monitor cardiac data points for patients. This expands the amount of data and the variety of environments that AI models may utilise, which may make it possible to detect cardiac episodes outside of hospitals early. Another quickly developing area of research is the use of AI for the categorisation and diagnosis of heart sounds.

Dermatology:

Dermatology is a speciality with a wide range of imaging options. Deep learning has been intimately linked to advancements in image processing. Thus, dermatology and deep learning complement one other effectively. The three primary imaging modalities utilised in dermatology are contextual, macro, and micro pictures. In terms of deep learning, each modality demonstrated noteworthy advancements. Han et al. have demonstrated that keratinolytic skin cancer may be recognised from facial photos. An artificial intelligence system that uses a deep learning convolutional neural network may be able to detect face skin cancer more accurately than dermatologists, according to a 2018 study published in the Annals of Oncology journal. Using photo processing, human dermatologists were able to identify 86.6% of skin malignancies on average, whereas the CCN machine was able to detect 95%.

Primary Care:

Primary care is currently one of the most important fields for the development of AI technology. AI has been used in primary care to support decision-making, predictive modelling, and business analysis. Despite the tremendous improvements in AI technologies, general practitioners have a relatively limited knowledge of the role of AI in primary care, mostly in regard to routine paperwork and administrative tasks. The clinical effectiveness of AI decision support systems used by physicians has not been prospectively assessed in many cases. Nonetheless, there have been cases where the use of these systems has improved the treatment choices made by physicians.

Psychiatry:

The field is still at the proof-of-concept stage when it comes to AI applications. The body of research is expanding quickly in a number of areas, including chatbots, conversational agents that mimic human behaviour and have undergone anxiety and depression testing, and predictive modelling of diagnostic and therapy outcomes. One of the difficulties is that many of the apps in this space are developed and recommended by for-profit businesses; one example of this is Facebook's 2017 introduction of suicide ideation screening. These applications, which are not related to healthcare, raise several legal, moral, and professional concerns. Other issues are usually with the models' validity and interpretability. Bias inherited by the models from tiny training datasets jeopardises these models' stability and generalisability. Furthermore, these models may be biassed against minority groups that are underrepresented in the data.^13,28.

Radiology:

Artificial intelligence (AI) is being studied in radiology to detect and diagnose diseases utilising computerised tomography (CT) and magnetic resonance imaging (MR). It could be particularly useful in situations when human experience is more needed than available or where the intricacy of the data makes it challenging for human readers to comprehend. Several deep learning models have shown the ability to diagnose diseases using medical imaging with an accuracy comparable to that of medical professionals. Few research that present these findings, meanwhile, have undergone independent validation. lowering image noise, enhancing MR image quality, and creating high-quality images with lower radiation dosages, and automatically evaluating image quality are examples of non-interpretative uses of AI for radiologists.

Telemedicine:

The expansion in telemedicine the practice of treating patients from a distance—has shown the potential for more AI use. By keeping an eye on medical data via sensors, AI can help with remote patient care. Constant patient monitoring and the ability to detect changes that might be harder for people to detect are possible with wearable technology. Artificial intelligence systems can compare the data to previously acquired data and notify doctors of any matters to be concerned about. Telemedicine's inclusion into standard health services is being hampered by the lack of scientific evidence demonstrating its clinical and financial effectiveness. 15. The British government has stated that without such evidence, telemedicine would not be widely used. It has been advised to policymakers not to advocate for funding untested technologies. Thus, studies that have found evidence of cost efficiency can be used to demonstrate recent advancements in telemedicine. The idea of telemedicine was first introduced in the early 1900s when doctors could advise patients over the phone and over the radio. Digital imaging, remote monitoring, and real-time video conferencing were made possible by the internet and other digital communication technologies that emerged in the late 20th century, completely changing the field of telemedicine.¹⁸

E Prescription:

Doctors are finding themselves more proficient with technology that take the place of something as fundamental but significant in medicine as writing prescriptions as medicine becomes more technologically advanced. A computer-generated, sent, and completed medical prescription is known as an e-prescription. Its primary goal is to lower the number of paper prescriptions and the possibility of inaccuracy that comes with written prescriptions.The primary danger of a handwritten prescription is that it might not be legibly written, which could cause pharmacists to read it incorrectly and cause the patient's death. Additionally, a paper prescription has the potential to be destroyed or lost. E-prescriptions don't have any damaging hazards. As a result, proper medical records are kept. The electronic prescription exchange between doctors and pharmacists is the goal of e-prescription.

E-prescribing software that assists doctors in managing patients, writing prescriptions tailored to their diagnoses, and completing different drug benefit checks.¹⁶ E-prescribing software assists doctors in managing patients, creating prescription diagnoses, and completing drug benefit checks.

Future scope of Medical Technology:

The COVID-19 pandemic hastened the evolution of technology in the healthcare industry. Patients can now obtain medical treatments outside of the traditional medical shop more quickly and easily. Structure improves everyone's access and convenience. Patients no longer need to visit the doctor in order to obtain care thanks to telehealth. Furthermore, remote patient monitoring is growing in acceptance across the globe. Over the course of the pandemic, wearable technology has become incredibly popular. It can now perform amazing tasks like remote echocardiograms and vital sign monitoring. If not for the outbreak, the state of the healthcare business probably would have taken another ten years to reach its current level. Even while our industry still has a lot to do in terms of technology, recent developments have placed it in a fantastic position for innovation and growth. Companies that supply medical technology have a fantastic opportunity to offer tools that will help physicians and patients alike. Predictive analytics, improved patient transparency, and integrated data interchange will likely become essential elements of healthcare in the coming year and beyond³².

Technological Challenges: The biggest barrier to adoption of new technologies in healthcare industry is first error rate. New technology goods usually require iterations before they are adequately trustworthy. This iterative technique, while challenging, runs the risk of producing inaccurate estimates and inappropriate recommendations. To prevent, technologists and clinicians implementing new technology need to collaborate closely. In order to achieve reliability, they will need to work together to fully test new tools and develop incredibly safe procedures.

CONCLUSION AND SUMMARY:

The conclusion of this topics is that. How medical technology is most important for in the healthcare sector. By using various new technology and advanced knowledge we can improve the healthcare facility and delivery for treatment and diagnosis. And another objective of this is that how we can improve in this field and how can we use new technology for curing disease and the providing facilities to the needy. There is lot lots of technology are in the road of development an various new technology will be come into existence in this field that are benefits for the population.

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Received on 09.08.2024 Revised on 13.01.2025

Accepted on 21.04.2025 Published on 15.05.2025

Available online from May 17, 2025

Research J. Science and Tech. 2025; 17(2):183-189.

DOI: 10.52711/2349-2988.2025.00026

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.