There has been an increase in the use of artificial intelligence (AI) technologies throughout the globe. Large corporations and individuals alike are embracing it. One step further, AI is being developed for application in the healthcare sector. All of the diagnostic data will be gathered and utilised to better understand illnesses so that more effective treatments may be developed.
Patients will appreciate the convenience as well. Doctors will be able to view a computerized copy of their medical history. As a result, patients may get medical advice from the comfort of their own home. In certain cases, physicians may want to alter their patient’s records. It’s not difficult for them. It will also safeguard the privacy of individuals’ personal information.
As a result, let’s take a closer look at AI’s role in healthcare progress.
HISTORY
Dendral, the first problem-solving software or expert system, was developed in the 1960s and 1970s. Although it was intended for use in organic chemistry, MYCIN, a system widely regarded as one of the most important early applications of artificial intelligence in medicine, was built on its foundations. There was no widespread adoption of systems like MYCIN by practitioners, as well as others like INTERNIST-1 and CASNET in the medical field.
In the 1980s and 1990s, microcomputers proliferated and new degrees of network connection were introduced. There was a growing understanding among academics and developers at this time that AI systems in healthcare must be built to handle imperfect data and draw on the experience of doctors. Systems for intelligent computing in healthcare have used approaches such as fuzzy set theory, Bayesian networks, and artificial neural networks.
Medical and technological advancements occurring over this half-century period that have enabled the growth of healthcare-related applications of AI to include:
- Faster data collecting and processing thanks to increased computer capability.
- Genomic sequencing databases are expanding in number.
- Electronic health record systems are becoming widely implemented.
- Computer vision and natural language processing have advanced to the point where robots can mimic human perceptions.
- Enhanced surgical accuracy with the use of robots
- Deep learning algorithms and data logs for uncommon illnesses are becoming better.
For illness prevention and diagnosis, AI algorithms may also be utilised to examine massive volumes of data from electronic health records. Artificial intelligence (AI) algorithms have been created for several medical organisations like the Mayo Clinic, the Memorial Sloan-Kettering Cancer Center, and the British National Health Service (NHS). In addition to IBM and Google, large technology businesses have created AI algorithms for healthcare. Hospitals are turning to AI software to help operational efforts that boost cost savings, improve patient satisfaction and meet their staffing and workforce demands. Artificial Intelligence (AI) in healthcare is now receiving billions of dollars from the United States government. Increasing utilization, minimizing patient boarding, reducing stay time and optimizing staffing levels are some of the methods being developed by companies to assist healthcare management in their daily operations.
HOW IS AI USED IN HEALTHCARE?
AI has a plethora of advantages over conventional methods. So, let’s have a look at some examples of how AI in healthcare might be beneficial.
- Human error will be reduced since doctors are less weary, which is a common problem in their line of work. It’s always important for them to pay attention to the tiniest details of their patients. This has a detrimental effect on the patient’s ability to function and is even deadly in some cases. It’s because of this that AI can assist people with some of the more difficult jobs, such as data arranging and examination. Using this method, physicians will be able to work more efficiently and avoid exhaustion.
- When a patient needs surgery or treatment right away, having this information is crucial to make an appropriate choice. Artificial intelligence will come in handy in these situations. Whereas physicians must go through the patient’s past data to determine the best course of treatment, AI can do it in a matter of seconds. As a result, you’ll save time and be more equipped to make decisions.
- Another advantage of virtual health aides is that they are helpful to both physicians and patients. Doctors may use it to examine data and make recommendations. By reminding people of their medication, aiding with diets and delivering health status updates to physicians, it may also benefit patients.
- By automating a number of routine processes, physicians may free up more time to focus on patient care. As a consequence, therapy is more effective and takes less time. The findings of MRI, CT scans, ultrasounds, and other types of imaging tests may be provided by AI, which cuts down on the time it takes to do the test and provides the results more rapidly. Patients don’t have to wait weeks for a test result since they may obtain it in just a few hours.
- You don’t have to rush to the hospital to show your medical report to physicians, saving you money. Isn’t it a way to save money? Personal assistants powered by artificial intelligence can help patients with medical difficulties. There is also the possibility of connecting people with physicians directly for guidance, lowering the expense of a trip to a clinic or hospital significantly.
- Automated diagnosis may also contribute in disease prevention by predicting the spread of illnesses at the macro level and also assessing the risk that a condition may be caught by an individual. This has the potential to improve patient outcomes while also assisting healthcare practitioners with a variety of administrative duties.
- Robotic Process Automation (RPA) has several advantages. According to Business Insider Intelligence, administrative chores account for 30 percent of healthcare expenses. Using Robot Process Automation (RPA) can help with a wide range of healthcare tasks, such as managing appointment requests from patients, registering patients, reviewing claims and payment integrity complaints, delaying payments and appealing denials and denials, and managing provider data and credentialing.
- Similarly, wearable healthcare technology employs AI in order to better serve its patients. Fitbits and smartwatches employ AI to analyse data and provide consumers and their healthcare providers with the most current information on possible health concerns and issues. Allowing people to monitor their own health through technology relieves pressure on medical staff by reducing the number of unnecessary hospitalizations and readmissions.
DEVELOPING THE NEXT GENERATION OF RADIOLOGY TOOLS
- Radiological images obtained by MRI machines, CT scanners, and x-rays offer non-invasive visibility into the inner workings of the human body. But many diagnostic processes still rely on physical tissue samples obtained through biopsies, which carry risks including the potential for infection.
- Artificial intelligence will enable the next generation of radiology tools that are accurate and detailed enough to replace the need for tissue samples in some cases, experts predict.
- We want to bring together the diagnostic imaging team with the surgeon or interventional radiologist and the pathologist,” said Alexandra Golby, MD, Director of Image-Guided Neurosurgery at Brigham & Women’s Hospital (BWH). “That coming together of different teams and aligning goals is a big challenge.”
- “If we want the imaging to give us information that we presently get from tissue samples, then we’re going to have to be able to achieve very close registration so that the ground truth for any given pixel is known.”
WILL AI REPLACE NURSES?
- What if robots one day take the role of nurses? In the end, the solution is disputed and raises a number of questions. Robots can have a beneficial impact on nurses’ life.
- Among the many tasks that the robots are programmed to do include taking vital signs, helping patients move about the hospital and giving drugs, as well as learning about infectious disease policy. All these benefits are becoming a reality, and robots are being steadily incorporated into healthcare environments, so it’s possible that the traditional function of nurses may alter.
- Most of the nurses’ workdays are spent on non-nursing tasks that may be handled to another member of the team. This percentage ranges from 8 to 16 percent, according to the research. Nurses will have more time to devote to their patients now that robots will be accompanying them.
- Sophia is the greatest example of a robot that has equaled the human level in terms of technology advancement. Known as the world’s most popular social robot, Sophia was created to be a friend for the elderly. This robot is a representation of the promise that technology has to improve the degree of humanlike operation that robots may achieve.
TELEMEDICINE
- The emergence of potential AI applications has been shown by the growth of telemedicine, the treatment of patients at a distance. Using sensors and AI, it is possible to provide remote care for patients. It’s possible that a patient’s condition may be closely monitored by a wearable gadget, which can pick up on subtle changes that people would miss. Data may be compared to other data that has been obtained using artificial intelligence algorithms that warn doctors if there are any risks to be aware of.
- Chat-bot therapy is another use of artificial intelligence. It is argued that the use of chatbots for mental healthcare does not provide the reciprocity and responsibility of treatment that should exist in a patient-caregiver relationship (whether it a chat-bot or psychologist).
- Since life expectancy has increased, artificial intelligence may be valuable in helping to care for the elderly. A person’s usual actions may be identified using tools like environment and personal sensors, which can inform a caregiver if a behavior or a measured vital is odd. There are debates regarding how much surveillance is permissible in order to protect people’s privacy, even if technologies exist to map out homes and detect human interactions.
INDUSTRY
Increased data accessibility is facilitated by the trend of big healthcare organisations combining. In order to apply AI algorithms, it is necessary to have a lot of data about health conditions.
Clinical decision support systems are a major area of industry interest for AI adoption in the healthcare sector. In the future, machine learning algorithms will be better able to respond and solve problems, as more data is gathered. Big data is being explored by a number of firms in the healthcare sector. Numerous organisations are scouring the healthcare sector for new business prospects by focusing on “data evaluation, storage, administration, and analysis technology.”
The following are examples of large companies that have contributed to AI algorithms for use in healthcare:
- The Cleveland Clinic and Memorial Sloan Kettering Cancer Center are working together to create IBM’s Watson Oncology. Additionally, IBM is collaborating with CVS Health and Johnson & Johnson on the use of AI in the treatment of chronic illness and the discovery of novel drug linkages. Health Empowerment by Analytics, Learning, and Semantics (HEALS), a collaborative effort between IBM and the Rensselaer Polytechnic Institute, was launched in May 2017.
- With the help of Oregon Health & Science University’s Knight Cancer Institute, Microsoft’s Hanover project is able to anticipate the most successful cancer medication therapy alternatives for patients. The creation of programmable cells and medical picture analysis of tumour growth are among the other efforts.
- Data acquired through a mobile app by the UK National Health Service is being utilised by Google’s DeepMind platform to identify specific health hazards. NHS patients’ medical photos are used in a second NHS study to create computer vision algorithms for the detection of malignant tissues.
- Several medical systems and services are being developed by Tencent. A diagnostic medical imaging service driven by AI, WeChat Intelligent Healthcare, and Tencent Doctor are just a few examples.
- Next-generation neuroprosthetics have been developed by Neural ink, which are able to communicate with thousands of neuronal networks inside the brain.
- They’ve developed a technique that uses a surgical robot to inject a chip the size of a quarter into the skull to prevent further damage.
Future of AI in Healthcare
Now that we’re approaching the future of AI in healthcare, have you given any thought to what that future may look like? So, the answer is that AI has a bright future ahead of it.
- By 2025, a survey by Tractica estimates that the usage of 22 healthcare AI devices would bring in $8.6 billion in annual revenue.
- Artificial intelligence, machine learning, and the future of healthcare are all interconnected.
- From 2020 to 2026, the healthcare industry is expected to have a CAGR of 44,9% for artificial intelligence (AI).
- Artificial Intelligence (AI) will be able to analyse vast amounts of data in order to identify and correct problems in the structure of the human body by 2030.
- In the next several years, AI will have a significant impact on healthcare services. Doctors will benefit from hybrid models as they use them to diagnose patients, detect ailments, and so on.
- The doctor, on the other hand, will just have a less workload as a result. The doctor still bears the bulk of the burden. The healing process will move along more quickly and efficiently this way.
- As a result, AI is having a significant impact on the healthcare industry. As we have previously stated, AI will have a positive impact on doctors, nurses, and patients in a variety of ways.
Conclusion
So, in summary, we can conclude that AI is working hard to develop the healthcare industry. Medical professionals, such as physicians and nurses, as well as patients themselves, are benefiting from AI in the healthcare industry, which is speeding up recovery times for everyone involved. Patients will benefit from AI’s improved and more accurate diagnosis, which will save costs. Doctors may spend less time on administrative tasks and more time getting to know their patients and providing them with the care they need thanks to AI.
