The healthcare industry requires some fundamental changes. Several opportunities could benefit from the latest technology to treat chronic illnesses and incurable ailments. The latest technological advancements can deploy accurate, efficient, and effective healthcare solutions at the right time.
Artificial intelligence is making strides in every industry. We see numerous applications of AI technologies in business, retail, marketing, and manufacturing. Healthcare practitioners can benefit from artificial intelligence in ways unimaginable by the human brain. AI can improve existing services and infrastructure by providing patient care and handling administrative tasks. It can also foster diagnostic, pathological, and clinical challenges efficiently and swiftly.
It is only a matter of a few years before artificial intelligence replaces humans on a broad spectrum of healthcare tasks, such as medical trials, diagnosis, discovery, treatment, and invasive surgeries. A disease once thought incurable may eventually have a cure with a 100% recovery rate. All of this is possible with artificial intelligence.
For many, artificial intelligence (AI) is still a baffling concept. Before moving further, let’s find out what is artificial intelligence;
What is Artificial Intelligence or AI?
When machines and digital appliances show human-like intelligence and capabilities, it is called artificial intelligence. Computers have become smart enough to perform tasks and duties usually associated with and performed by intelligent beings.
For instance, with more accuracy and speed, a computer recognizes the voice, face, handwriting, etc., like humans usually do. Also, when a robot begins performing invasive heart surgeries, we call it the application of artificial intelligence.
Application of AI in the Health Sciences
Having learned the gist of artificial intelligence, we shall now see the impactful intervention of artificial intelligence in the healthcare department. Artificial Intelligence (AI) significantly enhances the health sciences through innovative applications, notably in healthcare software. AI-driven systems streamline diagnostics, personalize treatment plans, and predict patient outcomes with high accuracy.
-
Radiology Tools
Every individual undergoes a scan at least once in their lifetime, either ultrasound, MRI, CT scan, or X-rays. These noninvasive, painless procedures offer visibility of the internal functions of the human body. They detect tumors, cysts, lesions, cancers, and other conditions. Doctors read the findings from their systems and often make errors in judgment while doing so.
Diagnostic processes that rely on physical examination or biopsies cannot accurately depict the actual problem, which could further increase the risk of infections.
Artificial intelligence is enabling next-generation radiology tools and machines with human-like capabilities. These do not require tissue sampling or physical examination for a detailed and accurate diagnosis.
-
Less Reliance on Electronic Health Records
Electronic health records, or EHRs, are instrumental in clinical documentation, patient records, history, order entry, and other healthcare processes. For a long time, the healthcare sector relied on EHRs to document patients’ health records using effective healthcare solutions. It was the first step towards the sector’s digitalization, but it came with multiple issues, such as cognitive overload, user burnout, and extensive documentation.
The introduction of artificial intelligence reduces the reliance of medical practitioners and doctors on EHR. Instead, they choose intuitive and interactive interfaces along with automated routine processes. Artificial intelligence brings voice recognition and diction services that improve the documentation process.
Probable uses of AI in the future include
- Recording clinical encounters to index information
- Virtual assistants will enter the patient’s history by coming to the bedside
- Processing routine requests and tasks from the mailbox, such as medication refills
- Prioritizing the tasks and surgeries that require immediate attention instead of simple elective surgeries
-
Infection Control in Antibiotic Resistance Cases
Self-medication and overuse of antibiotics for uncomplicated infections foster the environment for superbugs and bacteria. Therefore, prolonged antibiotic use is a threat to people worldwide. Their bodies resist any treatment through antibiotics, further worsening the condition. These drug-resistant organisms can claim hundreds of lives in the hospital.
Electronic health records (EHR) help computers read data and identify infection patterns. They also highlight high-risk patients even before they start showing symptoms. Moreover, they rapidly notify doctors and send the most accurate alerts. Curbing the problem at infancy is the goal of artificial intelligence in medical sciences.
If you have a functional EHR system, you must use it to its full potential to create faster, more innovative solutions. Technology is here to help us find effective healthcare solutions.
-
Precise Analytics for Pathology
Whenever we have a medical issue, the first and foremost step is diagnosing the disease. Without an accurate diagnosis, the problem could get worse. Pathologists are the diagnosis specialists who provide diagnostic data for patient care.
70% of diagnoses and decisions are based on pathological findings and images. Even the data in EHR also comes from the pathology lab after running tests. The better the pathology findings and results, the more accurate and timelier the diagnosis. That is what AI aims to deliver.
Artificial intelligence gets in-depth of the image to dig out the results that may escape the eyes of a pathologist. Analytics can go as deep as the pixel level of large digital images to get to the root of the problem. Doctors may make a mistake, but machines don’t.
In the future, artificial intelligence can tell whether a cancer is slow-progressing or fast-moving. It can study the series of changes over time based on cell count and other factors. It will also dictate how a patient can be treated based on an algorithm instead of clinical staging and histopathologic grading.
If and when that happens, that will be a huge pathology and medical science breakthrough.
Additionally, artificial intelligence can identify features and areas of interest in the slides even before the pathologist reviews the data. Effective healthcare solutions will surpass redundant findings and move directly to the critical part, saving time, energy, and human lives.
-
Advancing Immunotherapy for Cancer Patients
Immunotherapy works best for people fighting autoimmune disorders and cancer. Immunotherapy uses the body’s defense system against malignancies and internal threats. That’s the way to eliminate stubborn tumors and cancers. It is less invasive, so people prefer it, but sadly, not everyone benefits from the current therapy options. Even more unfortunate is that oncologists cannot determine who will respond to immunotherapy. They seek precise and reliable procedures to find the best candidates for this option.
Also, machine algorithms can synthesize data based on every individual’s genetic makeup and DNA to understand who is a potential target for immunotherapy.
A recent development made possible by AI suggested that several cancer inhibitors resist proteins made in our immune cells. Since oncologists do not fully understand the biology of the disease, they cannot determine how to use the information to their benefit. To solve the recurring immunotherapy resistance, they require a larger sample size, machine learning algorithms, and analytics. They have cracked the basics, but much work still needs to be done.
-
Robotic Process Automation
The RPA has to be my favorite application of artificial intelligence in digitalizing manual tasks. Robotic simulations perform digital tasks for administrative reasons. They follow a human script. Compared to other applications and forms of artificial intelligence, it is the most fascinating, inexpensive, easy to maneuver, and transparent.
Many people argue that it involves an actual robot performing tasks with human-like intelligence, but mostly, these are computer simulations and programs automating the functions. They can significantly help in healthcare with repetitive tasks that are otherwise time-consuming and mundane.
In some cases, similar to RIMS, an actual robot may be involved in performing minimally invasive surgeries. It puts the entire community of surgeons at risk as they may one day not be required. That’s why data scientists fear that. RIMS or “Robot-assisted Minimally-Invasive Surgery” is a promising concept offering accuracy and dexterity.
Moreover, the surgeons will likely use motor controls to perform surgical procedures through precise movements of robotic hands in your body. They can also make small incisions using robots or guide them to do that. We can expect automated surgical procedures in the decades to come.
-
Clinical Trials
We are in a hot mess because of the unorganized and unaligned clinical trials. Most of them do not follow any standardized process to integrate the solution. So, there is no way one can judge the progress of the trials and phases. Drug trial outcomes are not conclusive because of a lack of data gathering.
Artificial intelligence can alter the course of clinical trials to ensure a systematic approach to the conclusion. Clinical trials can be perfected using predictive modeling based on previous research on similar genetic makeup, patient history, and medicinal formula. It will take care of the entire process, from enrolling candidates to medical adherence.
The best example of AI-driven clinical trials is the production of the COVID-19 vaccine during the pandemic. Pfizer used millions of data points from a sample size of 44,000. It also had data from earlier vaccine trials in an attempt to curb SARS. Integrating that data with recent findings helped formulate a potent COVID-19 vaccine.
Conclusion
It is crystal clear that artificial intelligence holds the power to forever change the dynamics of effective healthcare solutions. AI is involved in every process, from patient history, data recording, and disease diagnosis to performing surgical procedures, and it can do anything. It will take a few decades to perfect the process before we digitize the entire healthcare industry. It has already begun to unravel the marvels of science. So, wait and watch for more revelations.