AI-Assisted Decision Making Is The Way To Advanced Healthcare

Artificial Intelligence (AI) is poised to revolutionize healthcare. The accountability and transparency of AI-based systems’ judgments and the professional duties and integrity of doctors are among the key ethical challenges that have emerged as a result of this transition. These issues must be weighed against the imperatives of creating public benefit from AI’s significantly increased and precise computing capability through more efficient healthcare systems. 

Why are we starting off from the challenges? Well, it is the challenges that let us know the real depth of a revolution. Now, let’s take a closer look at the overall scenario of AI in Healthcare with the market statistics – 

The Market Outlook When AI Interfaces With Healthcare

Artificial Intelligence will play a significant role in medicine and healthcare. Many factors contribute to this, including advances in processing power, learning algorithms, the availability of enormous data from medical records, and wearable health devices. The healthcare industry for Artificial Intelligence is growing by the day, and market trends do appear to be positive.

According to studies, the value of AI in the global healthcare business is expected to increase from $8.23 billion in 2020 to $194.4 billion by 2030. It is predicted to increase at a CAGR (Compound Annual Growth Rate) of 38.1 percent from 2021 to 2030.

In 2019, the advertising and media industry topped the AI market, accounting for more than 20% of worldwide revenue. The healthcare industry is expected to take the lead in the AI market by 2027. 

It’s a better outlook overall! What say!? Well, if so, why not go a step further and decode the role of AI in the healthcare sector… 

What is AI in Healthcare?

The employment of Machine Learning (ML) algorithms along with advanced cognitive technologies in the context of healthcare is termed as AI in healthcare. In its most basic form, artificial intelligence (AI) occurs when computers and other robots replicate human cognition and are smart enough to learn, reason, and make decisions or perform actions. The use of machines to evaluate and act on medical data, generally with the objective of anticipating a certain outcome, is what AI in healthcare is all about.

The application of ML and other cognitive disciplines for medical diagnosis is a prominent AI use case in healthcare. AI may assist doctors and medical professionals in providing more accurate diagnosis and treatment plans by utilizing patient data and other information. Furthermore, AI may assist in making healthcare more predictive and proactive by analyzing large amounts of data to produce better preventative care suggestions for patients.

How is Artificial Intelligence Used in Healthcare?

With a large amount of data accessible, AI is positioned to be the force that drives revolution in the health industry. Learning Algorithms are getting more exact and precise as Artificial Intelligence allows us, humans, to obtain insights into diagnosis, therapies, and care procedures. Here are several real-world AI uses in medicine that can assist both patients and practitioners.

Quick Drug Discovery and Development:

AI is being used by leading medical and pharmaceutical businesses to decrease R&D expenditures and minimize costly blunders. Machine Learning can improve the efficiency of several analytical procedures in drug development. This has the potential to save millions of dollars in investments. 

The drug development process is segregated into 4 logical phases – 

Phase 1 – Identifying intervention targets

Phase 2 –  Finding pharmacological possibilities

Phase 3 – Acceleration of clinical trials

Phase 4 – Identifying biomarkers for illness diagnosis

Diagnosis of Diseases:

AI-powered software may determine whether a patient has a specific disease even before many obvious symptoms arise. And, in the vast majority of situations, these forecasts are correct. AI reduces the cost and accessibility of diagnostics. Machine Learning, particularly Deep Learning algorithms, is increasingly being utilized to autonomously diagnose illnesses. 

Machine Learning can be useful when it is about using CT scans to detect brain tumors or lung cancer. Moreover, it helps in the usage of ECG and cardiac MRI scans that helps assess the risk of sudden cardiac arrest or other heart illnesses. 

Advancement in Gene Editing

Artificial Intelligence is being employed in genetic research. Machine Learning methods are increasingly being used in genome sequencing and annotation, among other applications. And that’s not all. It’s also employed in genome-wide diagnostics. And if you believe AI won’t be able to modify our DNA, think again.

Digital Nursing Assistants:

Many of us, if given the choice, would avoid unnecessary hospital visits. But is it even possible? Yes, of course. With Digital Nursing Assistants. Virtual nursing assistants prevent needless hospital visits, easing the pressure on medical staff even more. Patients can benefit from a tailored experience provided by an AI-powered virtual nursing assistant. 

It can assist in identifying sickness based on symptoms, monitoring health status, scheduling doctor’s visits, and much more. It can keep any chronic condition from worsening. Virtual assistants are very popular these days. They are being used by hospitals and medical professionals to boost patient involvement and self-management abilities.

Varying medications and treatment regimens have different effects on different people. Patients’ lives can be extended significantly with individualized treatment choices. Machine Learning is utilized to deliver individualized care. How? It can assist in determining the features that suggest a patient will have a certain reaction to a given treatment. It can forecast a patient’s likely reaction to a certain therapy. 

But how does the machine learning algorithm discover this? The system learns this by comparing treatments and results of comparable patients and cross-referencing their data. This is extremely useful for doctors in developing the best treatment plan for the patient.

Why Should Healthcare Invest in AI Technology? 

Quick and Smooth Diagnosis

AI-powered solutions increasingly rely on people’s data to analyze patients’ past and present health difficulties. Healthcare providers can make more accurate diagnoses by comparing illness details. Several healthcare mobile applications’ databases have computed millions of symptoms and diagnoses. More significantly, it may forecast probable health difficulties that an individual may face in the future. 

Speed and Cost Efficient

Healthcare operations are now speedier and less expensive thanks to AI algorithms. From patient inspection to diagnosis, AI has significantly accelerated and reduced expenditures. For example, AI can find biomarkers in our bodies that indicate sickness. AI algorithms have reduced the amount of manual labor required to specify these biomarkers. Because of tremendous automation, we can now save more lives by responding quicker. 

Improved Accessibility

Most poor nations, which are striving to keep up with global technology breakthroughs, have little or no access to modern healthcare facilities and systems. The chance of death is higher for residents of such a country. These underserved communities can benefit from an efficient healthcare environment thanks to AI advancements. 

AI-driven virtual systems can aid in patient diagnosis as well as patient therapy. There is specific software designed to aid international and national healthcare institutions in collaborating and providing crucial support to those in need.

The Ideal Surgery Assistant 

In robotic applications, artificial intelligence development has made significant strides. The same is true for the use of machine learning in surgery. There are AI Surgical Systems that can execute the smallest moves with pinpoint accuracy. This implies we can do difficult surgeries with less chances of adverse effects, blood loss, or discomfort. 

Similarly, post-surgery recuperation is quicker and smoother. The finest element is the AI-backed information on the patient’s current state, which is available to surgeons in real-time. This has helped to alleviate patients’ concerns, particularly about surgery under general anesthesia.

Optimized Human Abilities And Mental Health Support

Robots can now aid patients alongside medical personnel. For instance, 

  • Exoskeleton Robots: It can assist paralysed patients in regaining movement with little or no assistance from caregivers. 
  • Intelligent AI-powered Prostheses: These bots are outfitted with sensors that behave as more reactive limbs than previous versions. 
  • Service Robots: Based on machine learning that can conduct everyday duties and keep patients company. 
  • Conversational Robots: These robots do required tests and checks – sugar levels, blood pressure, temperature regulation, and even pill intake. Because of their built-in analytic skills, robots have been designed to assist depressed patients. They can examine the mood of the patients and assist them feel more optimistic using these talents.

Way Ahead For AI-Based Decision-Making In Medical Field

Given its vital role in a productive, healthy society, healthcare is one of the most critical areas in the larger landscape of big data. The use of AI to healthcare data can actually mean the difference between life and death. AI can help physicians, nurses, and other healthcare professionals with their regular tasks. 

AI in healthcare may improve preventative care and quality of life, provide more accurate diagnosis and treatment plans, and result in overall improved patient outcomes. By analyzing data from government, healthcare, and other sources, AI can also anticipate and track the spread of dangerous illnesses. As a result, AI has the potential to play an important role in global public health as a tool for combating epidemics and pandemics.

Guest article written by: Heena Soni is an avid researcher and writer at, a Technology Company working on digitalizing industry processes for varied domains. Being a part of the content management team, she is enthusiastic about advanced technology and likes to be updated on the latest know-how of technology.

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