Most of us are aware of the milestones covered by artificial intelligence. The level of growth and advancement in various fields has been quite prompt, and often unpredictable.
So, what is artificial intelligence? How will it completely transform the healthcare industry in the forthcoming years? What are the pros and cons of incorporating it into healthcare.
Find answers to all these questions right here!
What is Artificial Intelligence?
Artificial intelligence (AI) is an extensive branch of computer science associated with developing smart machines capable of executing tasks that usually require human intelligence.
AI is a multidisciplinary science with various approaches, but evolution in machine learning and deep learning are establishing a paradigm shift in virtually every sector of the tech industry, including healthcare.
Machine Learning And Neural Networks
Machine learning is based on modern artificial intelligence and is primarily an algorithm that permits computers to learn autonomously without following any specific programming.
Since machine learning algorithms confront more data, the algorithms’ performance gets better.
Deep learning is a branch of machine learning that works in a similar way with a slight modification. Deep learning goes a step ahead, making interventions on the basis of the data it has confronted before.
In other words, deep learning allows an AI application to make its own conclusions. It functions through an artificial neural network, which is a set of machine learning algorithms that operates in pairs.
A neural network roughly resembles the human brain, with a whole range of “neurons” that “fire” when some stimuli (in this particular case, data) are available.
Traditional machine learning solutions aren’t intellectual; they are skilled from data but lack the capacity to leap beyond broken or missing data and formulate a hypothesis about potential action.
Machine learning could be effective in sensing something that’s expected, but it fails when encountered by the unexpected.
How Is Artificial Intelligence Used In Healthcare?
Electronic Health Records: Undoubtedly, electronic health records (EHR) brought out tactical changes in the healthcare industry, but it wasn’t proved to be a smooth changeover.
It has some limitations, including cognitive overload, endless documentation, and user burnout. On the contrary, artificial intelligence can actually automate all these tedious and routine processes and make the interface intuitive.
Medical documentation is very time-consuming but with the potential of dictation and voice recognition, conjugated with natural language processing (NLP), a great deal of time and effort can be saved.
This is a great blessing for doctors because information extraction is a major aspect of artificial intelligence. And there is an even intuitive user interface to make it simpler for storing information.
There is also a significant change in the way patients are treated. Doctors no longer need to worry about medicine overdose or wrong combinations or allergies because these details will all be stored in the cloud, depending on, and acted upon at the appropriate time.
Patients with a history of infections can also benefit from this technology as it is now way too easy to detect the pattern and send notifications.
In addition to information storage and retrieval and detection of patterns, AI can manage routine requests also. Consider the following things:
Let’s say a patient has an overdue lab test; it would send notifications to the relevant patient.
Find out which patient out of all requires immediate assistance and prioritize them on that basis.
A patient is on the brink of running out of his medicines; the medication refill request will be transmitted without delay.
Medical Imaging Diagnostics
AI plays a crucial role in allowing intelligence in the radiology pictures produced through scanning machines.
CT, scanners, MRI machines, and X-rays give an overview of the body’s internal mechanisms, but they are not sure-fire because they cannot always provide a precise diagnosis on their own.
Healthcare providers usually had to depend upon alternate or supplement techniques (such as biopsies) to draw better conclusions on what is not right with the patient.
But artificial intelligence has wholly remodeled the scanning machines’ downsides by supplying highly precise inputs on the body.
The diagnostic imaging team, including the pathologist and the doctors, may reach a unanimous conclusion on the treatment method, and the odds of surmounting obstacles are very high.
It can study the various diagnostic images and check for abnormalities. Deep learning algorithms have made it feasible to distinguish between cancerous and non-cancerous cells in a far better way.
Radiologists now can zoom into a specific problem and analyze it more accurately, do something better than what the human eyes might do, even with the support of high-end scanning equipment, and identify tumors, infections, and bleeds.
By monitoring the affected site intensely, healthcare providers can make better decisions on whether the treatment will impact the surrounding areas or how deep the infection might go and indicate possibilities of the disease.
Now the surgeon could easily examine the addicted area and go deeper into it.
Surgeons are also helped in a way that they are now able to get more precise inputs on how they can access the surgical area.
Virtual Health Assistants
The primary reason for adopting virtual nursing assistants has been the lack of medical labor which generally causes pressure on the available health professionals.
A virtual assistant powered by AI can improve the communication between patients and care provider while resulting in a better consumer experience and decreased physician burnout.
When medical professionals seem to be taking time with their patients, the latter end up feeling cared for and have a sense of satisfaction.
A virtual assistant can execute an initial discussion between the patient and physician, setting the pace for more detailed conversations later. In this way, a virtual assistant for healthcare could take physicians’ responsibilities, enabling them to concentrate on offering better service and care.
Visual health assistance help patients in numerous ways; some of them are listed below:
- Remind patients to take their medications at the right time
- Offer medical advice when they have common illnesses or complaints
- Remind them of doctor appointments and manage bookings
- Suggest diet and eating habits for people with diet restrictions
- Allow virtual interaction with doctors
- Remind when they are about to run out of medicines and order prescriptions
Some chatbots advise the family member or caregiver of the patient to offer correct primary healthcare who requires immediate medical assistance, at least until paramedical staff takes over.
It is also likely for patients to visit medical websites and chat with the chatbots, discuss the symptoms they’re experiencing, and ask health-related queries.
The chatbots themselves are so intellectual that they are adjusted to interpret and reciprocate user sentiments. They can act just like a healthcare provider if the need emerges.
Yes, the chatbots can never substitute the typical doctor, although they can at least help reduce the stress and worries encountered by the patient.
Will you be comfortable with a robot performing surgery on you? Perhaps not! You would feel much better when a qualified surgeon does the procedures.
But, how about combining the skills of a skilled surgeon with the technical intelligence of a robot? This will make the surgery executed with commendable precision, accuracy, and steadiness.
And when you have AI directing the hand of the surgeon through the assistance of robots, it paves the way to very high levels of authenticity and better patient results.
The AI assistant could immediately provide details on the patient’s past and present medical records and make recommendations that would aid in the diagnosis.
Surgeries have turned into minimally invasive techniques whereby hospital stay is substantially reduced. There are surgical bots that employ computer vision to correctly conduct surgeries after computing the human body’s measurements.
AI helps with surgeries of different capacities, including procedures with varying degrees of complexity. And this might have a significant impact on hospital stay, and consequently, the recovery of patients.
When a surgeon carries out a complicated surgery, AI supplies him/her with real-time data to detect and alleviate risk and enhance quality.
The robot hands make highly accurate movements, so any shakes in the surgeon’s hands will be counterbalanced completely, enabling the advancement and success of microsurgeries.
And the best part? The AI system will keep tracking the patient and his health levels long after the medical professionals and nurses have gone to sleep. Human constraints will never be a concern in producing worthy patient outcomes.
Proactive Medical Care
In conventional medical treatment, the trend was to treat the patient after the disease is diagnosed. For instance, if a patient consults a doctor with certain symptoms, the doctor might do some specific tests and then identify the patient has cancer.
Treatments like chemotherapy or radiation therapy are started later. Likewise, a patient consults a doctor with diabetes symptoms, and the doctor orders the tests and then prescribes medications or insulin shots. This type of treatment is known as reactive medical care.
With Artificial Intelligence, there has been a great transition in this trend as reactive medical care became proactive medical care. In this type of care, the patient’s full health history is studied, and significant risk markers for different diseases are indicated.
At risk, patients are then examined for any change in their conditions, and if anything seems terrifying enough, the app can propose medical intervention.
There are several apps that you may use to be an active participant in your own health. Therein you’ll find some tips that you can follow each day to improve your condition and achieve good results.
Understanding How AI Will Help Accomplish Different Tasks
There are two types of artificial intelligence devices, Machine Learning (ML) and Natural Language Processing (NLP). The first category, machine learning, works to scrutinize structured data, including genetic, imaging, and electrophysiology data.
In healthcare, it implies clustering patients’ traits and reviewing the possibility of diseases.
The next category is natural language processing, in which unstructured data is accessed from different sources such as medical journals and clinical notes.
This data will then be transformed into machine-readable structured data, which will then be studied with machine learning techniques. The powerful AI activities make it possible for patients to enjoy precise and timely decision-making.
This is done through early detection, where the patients are examined using Electronic Medical Records (EMR).
The doctors can now save all their notes in digital formats. In the same way, cans, X-rays, and imaging tests are also computerized.
Healthcare providers will then find an appropriate diagnosis with the help of machine learning and other AI techniques and start the treatment immediately.
What Are The Pros & Cons Of Incorporating AI In Healthcare?
- AI aids healthcare accessibility
- AI-driven tools help expose early disease risks
- AI algorithms help save time and costs
- AI is unique and unparalleled assistance in surgery
- AI helps reinforce human capabilities and improve mental health
- A lack of personal involvement
- An increment in unemployment rates among healthcare workers
- Probability of an incorrect diagnosis
- May not concur with social prejudices