Note from our Author
This subject was interesting to me because when I look back on stories of my grandma working in hospitals without things like computers and traditional instruments, it's just amazing how fast technology developed to the point where now, computers are a commodity and scientists are developing machine-learning softwares in microscopic chips implantable in brains. I think it's really cool that as technology gets more advanced, the medical industry is implementing new devices and things like digital healthcare are becoming a reality, helping patients across the globe by making healthcare more affordable and accessible!
Revolutionizing Healthcare: The Impressive Impact of Advanced Technologies
Technology in Healthcare
With the recent rise of technology, advancements in the medical industry have also been substantial. Artificial intelligence, neural chips, and machine learning systems are being developed and improved over time to be used on humans to treat diseases and disorders more efficiently and reduce health and safety risks.
Aritificial Intelligence
Benfits
Artificial intelligence (AI) is the intelligence of machines that is similar to that of humans. This technology has recently grown in popularity through social media and things like chatbots that implement AI to hold human-like conversations with users. But AI has also been used in healthcare, to diagnose diseases and conjure tailored solutions to certain problems. It has been previously used during the rise of the coronavirus disease 2019 to “drive systems that process computed tomography scans by the thousands…” (Thomas, 1). Furthermore, AI has been used in the pharmaceutical industry to help go through chemical libraries to find new drug candidates and can replace experiments with simulations to alter certain parameters to view different outcomes. Artificial intelligence is not only much faster than traditionally experimenting and searching libraries of chemical combinations, but it is also more economical.
Dangers
Although artificial intelligence is very promising for future dependency in the medical industry, it also poses some threats. Since it is a digital technology (software/machine intelligence), it can be hacked or warped to steal information such as patient data and provider identities and divert funds. “This can occur via private systems linked to hospital software, or by wireless networks at health facilities, or via the Internet of Things (IoT)” (Thomas 1). Because of this, it is imperative that security measures be taken when AI is used in healthcare, which can be quite expensive, and possibly cost more than what is saved by using AI initially. Staff must be trained and monitor artificial intelligence systems that are used in healthcare, and install security systems to prevent or locate data breaches.
Brain-on-a-Chip (BOC) Devices
While artificial intelligence is a more versatile tool for healthcare, microfluidic brain-on-a-chip (BOC) devices are a more specialized technology focused on enabling scientists to screen drugs while avoiding differences in species that can inhibit the development of new drugs. Traditionally, in studies conducted on living organisms on test tubes or dishes, animal studies have been done to understand the development of and the processes involved in brain diseases. This allows scientists to work on treatments that can effectively cure these diseases. However, due to species differences between animals and human subjects, drugs have been failing in clinical environments. The microfluid BOC is a piece of technology that allows scientists to use human tissues for experiments, overcoming the differences between species issue. The BOC devices also allow for the screening of new drugs. Although this technology seems promising, due to the brain’s complex nature and environment, the BOC must be integrated “with new sensors that have high sensitivity and selectivity…” (Zhao et al., 1) in order to detect changes in such as neurotransmitters and other cerebric molecules. BOCs have not been studied in humans, however, for ethical and technical reasons and other challenges still stand in the way of BOCs being implemented in medicine, such as the lack of real-time monitoring in the brain. In conclusion, BOC devices are advancing rapidly, and with the use of sensors, the BOC’s analytical capabilities are even better; its implementation in medicine can lead to greater simulation of brain tissue and its microenvironment, as well as a reduction in animal and human experiments.
Neuro-Chip
A chip like the BOC devices, NeuralTree is “a closed-loop neuromodulation system-on-chip that is capable of detecting and alleviating symptoms of disease” (Lausanne, 1). The chip has a high-resolution sensing system as well as a machine learning processor, which together can accurately predict symptoms of diseases. The chip works by extracting neural biomarkers from brain waves, which are associated with certain brain diseases, and classifying them to identify possible upcoming symptoms such as seizures or Parkinsonian tremors. When a symptom is detected, a neurostimulator on the chip proceeds to send an electrical pulse to block it, effectively alleviating symptoms of brain diseases.
The neuro-chip is one of the most recent and efficient brain technologies in healthcare and is equipped with 256 input channels - an improvement of over 200 compared to previous machine learning technology. This refinement allows the chip to process high-resolution data, as previously stated. Furthermore, since the chip is so minuscule, it is extremely area-efficient and versatile, and scalable to adapt more input channels. Along with its microscopic area, NerualTree’s energy-aware learning algorithm makes the technology energy efficient as well. Compared to previous technology, the neuro-chip is able to efficiently detect more symptoms; its algorithm, trained with data from individuals with Parkinson’s disease and epilepsy, is able to accurately classify pre-recorded signals from both these diseases. One of the chip's creators, Mahsa Shoaran, aspires to make neural interfaces more intelligent to regulate and restrain diseases more effectively. She desires to develop an algorithm that updates autonomically inside the chip itself, keeping up with changing and evolving neural signals to prevent the neural interface from declining over time. This way, in the near future, the chip’s algorithms will be more reliable and accurate, reducing the risk of brain disease symptoms, and taking neurology to an entirely new level.
Digital Healthcare
Aside from state-of-the-art technology like NeuralTree and BOC devices, things like mobile devices that are commonalities in the modern information age can also be implemented in the medical industry, as digital healthcare rises in popularity. The rise in technology has led to the development and implementation of mobile health (mHealth) technology. “mHealth is defined by the practice of medicine supported by portable diagnostic devices” (Bhavnani, Narula, & Sengupta, 1). This innovation is revolutionizing healthcare delivery, making it more patient-generated. This change creates new opportunities for the healthcare industry to expand patient engagement, reduce expenses for healthcare, and improve overall outcomes. Although further validation of mHealth and its impact on healthcare is still required, mHealth provides a promising idea to revolutionize digital healthcare. Health conditions including heart failure, diabetes, and hypertension, as well as medication adherence monitoring, have seen benefits due to technology. Additionally, as technology evolves in healthcare, data transfer becomes more and more vital for implementing mHealth into clinical environments and real-world medical practices.
iECG
One example of technological innovation is the iECG, which is essentially a smartphone case for wireless cardiac telemetry monitoring with electrodes. The device displays the user’s cardiac rhythm in real-time, and it includes automated algorithms “...which provide the user with an immediate rhythm analysis of atrial fibrillation” (Bhavnani, Narula, & Sengupta, 1). Individuals at a high risk of developing an arrhythmia are recommended to use the iECG, as the device conveniently and efficiently delivers analyses of cardiac rhythms. “The iTRANSMIT investigators demonstrated a 100% diagnostic accuracy of the iECG to detect the recurrence of an atrial arrhythmia after an ablation when compared with traditional transtelephonic monitoring” (Bhavnani, Narula, & Sengupta, 1). Furthermore, the iECG is highly economical and practical, as is most other technology in digital healthcare. Technology is improving the medical industry by reducing patient expenses and increasing the accuracy and efficiency of treatments and analyses for certain disorders, diseases, or conditions.
Wireless Devices
Similar to smartphone devices, continuous blood pressure, and glucose monitors have been developed. These devices take a portable form, such as in a watch, and are wireless and wearable for users. The monitors have been useful for individuals with drug-resistant hypertension or orthostatic hypotension. Additionally, “Continuous glucose monitoring (CGM) with minimally invasive sensor technologies…” (Bhavnani, Narula, & Sengupta, 1) is another technological instrument that is effective in diabetic patients in which they are able to monitor glucose levels in real-time. CGM effectively prevents hypoglycaemic episodes and can control glycemia in the long term through behavioral changes such as those in diet, exercise, and taking medication.
Telemedicine
Telemedicine is healthcare delivery through electronic information and technology, over a long distance. Along with mHealth, telemedicine, through things like smartphone applications and text messaging, are cost-effective and accessible methods of promoting individuals to quit smoking, improve medication adherence, prevent diabetes, and improve results in patients with coronary heart disease. Users can also measure themselves through mHealth; these measurements have been linked with improvements in blood pressure and glycemic control in hypertensive and diabetic patients. Furthermore, trials regarding telemedicine have indicated improvements in heart failure patients, as well as a reduction in hospitalization and a boost in survival rates (although some trials have shown no difference in outcomes). This difference in outcomes may be a result of patient classifications rather than things to do with the devices. All in all, telemedicine is a great way to aid patients with certain conditions and with measurements they can do individually rather than having to come to a hospital. Although finding a match between patients and digital technology is needed to determine how effective telemedicine is, it is economical and convenient, as well as a highly accessible alternative method in healthcare.
Conclusion
We live in the digital age, a time in which computers and digital technology are rapidly being developed and evolving. And along with the evolution of technology, other industries such as medicine and healthcare are advancing as a result. Improvements in technology allow new instruments and technology to be implemented in healthcare, including neural chips, artificial intelligence, and mobile healthcare. Devices that can be used for things like entertainment can be applied in the medical field to aid patients in self-measurements and analyses. As technology progresses, the accuracy, reliability, and overall outcomes in clinical environments increase as there is less room for human error. Digital healthcare is improving continuously, as medicine evolves to become more personalized and refined.
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