A Complete Guide on the Role of AI in Healthcare

Healthcare industry has benefited a lot from the great advancements in the field of technology. In fact, artificial intelligence or AI can significantly impact the healthcare industry. To understand the impacts of AI in the healthcare industry, one must know exactly what artificial intelligence is and what are the different areas where it is used to make healthcare better. Here is the list of technologies where artificial intelligence has taken over.

1. Scanning and Ultrasound Technology 

AI can assist clinicians in taking a more comprehensive approach to disease management, better coordinate care plans, and help patients to better manage and comply with their long-term treatment programs, in addition to helping providers identify chronically ill individuals who may be at risk of an adverse episode.

By examining the metadata in a document, artificial intelligence may classify it using more sophisticated optical character recognition (OCR) techniques. This is the best technology that has automated file scanning, document classification, and precise processing.

AI-powered ultrasound technology offers the potential to speed up the widespread application of medical ultrasound in a range of clinical contexts. AI models can account only for information ‘seen’ during training, so in this example, non‐imaging clinical information is not taken into account by the AI model. Hence, an important emerging area of healthcare AI research focuses on building AI models that integrate imaging and electronic health record data for ‘personalized diagnostic imaging’.

So far we have understood the role of AI in healthcare in Scanning and ultrasound technology, proceeding ahead, we will learn more about managing customer records

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2. Managing Customer Records

In the healthcare sector, gathering and analyzing data, such as past experiences and medical records, typically represents the first phase. Data administration may be greatly streamlined by integrating artificial intelligence and digital automation.

Robots are being employed to gather, re-format, store, and trace data to make information access quicker and more reliable. Reputable IoT solution companies have been working closely with hospitals and other healthcare organizations to develop tools that combine strong AI.

One of the upcoming Big Data frontiers that needs to be conquered is healthcare. Significant and useful data may get lost in the massive data collection like a needle in a haystack, costing the industry billions of dollars annually. In addition, the creation of accurate diagnoses and new medications and medicines is slowed down without the ability to connect crucial data pieces.

A number of healthcare companies have turned to AI in healthcare to stop the loss of data. They can now segment and connect the necessary data using AI, which used to take years to handle. 

3. Robotics Assisted Surgeries 

For more than 30 years, medical robots have been in use. They range from basic laboratory robots to extremely sophisticated surgical robots that can work alongside a human surgeon or carry out procedures on their own. They are used in hospitals and labs for repetitive jobs, rehabilitation, physical therapy, and support for people with long-term problems in addition to surgery.

Robots have the potential to completely transform life care by enabling patients to maintain their independence for longer and decreasing the need for inpatient care and nursing facilities. AI is making it possible for robots to go even further and interact socially with humans to keep aging minds sharp through "conversations" and other social interactions.This is how the role of AI in healthcare advances the field of Robotics.

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4. Drug Research and Discovery

AI helps pharmaceutical industries in drug design and also assists in deciding the right product for the machine. Artificial intelligence-enabled drug development systems are assisting businesses in utilizing massive amounts of data to swiftly identify patient response markers and create more effective and affordable appropriate treatment options.

One of the most interesting uses of AI in healthcare now is the integration of biotech platforms. Machine learning is being used by several pharmaceutical companies, including Pfizer, to find immuno-oncology treatments. They are attempting to identify new combinations of medicinal ingredients for creating novel pharmaceuticals by looking for trends in medical data and examining the effects of current medications on patients. Researchers and AI engineers are attempting ground-breaking approaches to find new medications and vaccines to treat chronic and a variety of other ailments with the help of some extremely advanced projects that are currently available online.Now we know the role of AI in healthcare in terms of Drug research. Let us see what more AI in healthcare can change.

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5. Healthcare Assistants

Virtual health assistants are in charge of a variety of tasks, such as answering routine patients' calls and emails and keeping their medical information while protecting sensitive data, setting up doctor appointments, reminding patients of follow-up visits and clinical meetings, etc.

Systems using cognitive computing, augmented reality, and body and voice movements are combined to generate this. Cognitive computing and augmented reality helps to stimulate and solve complex human thoughts. It is one of the most helpful AI in healthcare that provides patients with a tailored experience in managing their health and removing their questions. Both patients and medical professionals gain from the decrease in hospital visits.

When it comes to early diagnosis of potentially blood-related disorders, artificial intelligence is a huge asset. Doctors are now able to check for dangerous compounds and germs in blood samples, such as Staphylococcus, E. coli, etc., at a far faster rate than they could with manual scanning thanks to AI enhanced microscopes.

For the machines to learn how to locate the dangerous bacteria, researchers examined more than 25,000 pictures of blood samples. With the use of AI, the robots were able to learn to recognise these bacteria in the blood and predict their existence in fresh samples with a 95% accuracy rate, significantly lowering the fatality rate.

7. Treat Neurological Disorders

Diseases associated with the peripheral and central nervous systems are known as neurological disorders. Pattern recognition uses a variety of ML algorithms. Automatic classification typically assists clinical decision-making on a brain pathology or many classes of it by identifying patterns that match to classes.

For instance, classification techniques based on anatomical data are frequently used to identify Alzheimer's disease (AD) and other forms of cognitive impairment.

8. Medical Data Analysis

AI is organizing medical data using deep learning and reducing methods to give clinicians and medical researchers a better grasp of the vast repository of medical data. AI is assisting scientists in tracking and advancing medical research by removing redundant methods of data analysis and manual data filtering. This includes processing and analyzing clinical trials to find the effects of vaccines, drugs, and other treatments as well as tracing the origins of virus strains.

Now that we know the role of AI in healthcare in the field of Medical Data Analysis.

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9. Cancer Diagnosis 

AI is already being used to more precisely and early diagnose diseases like cancer.The National Cancer Institute claims that deep learning, machine learning, and artificial intelligence can all be utilized to enhance cancer treatment and patient outcomes. Over 13,000 colorectal cancer photos were collected by the researchers from 8,803 participants and 13 separate cancer facilities in China, Germany, and the United States. The researchers then created a machine learning software using photographs that technicians randomly selected.

A study suggests that,The software can identify colorectal cancer photos, which is one of the leading causes of cancer-related fatalities in both the US and Europe.

10. Diagnosing Covid-19 

By quickly analyzing massive amounts of research data, AI technologies and methodologies can aid in the understanding of the COVID-19 virus and speed up research on remedies. AI text and data mining techniques can find out about the virus's origins, spread, and diagnosis, as well as on management strategies and lessons learned from other pandemics.

AI can also be used to track down the infection, diagnose it, and stop it from spreading. The spread of COVID-19 is already being detected and predicted by algorithms that recognise patterns and anomalies, and image recognition systems are accelerating medical diagnosis. For instance:

Early warnings can be provided by AI-powered early warning systems by mining popular news, internet content, and other information channels in several languages. This can augment syndromic surveillance and other healthcare networks.

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AI is aiming to improve healthcare for the general population by leveraging real-time data to optimize anything from ambulance routes to waiting times. The development of chatbots to aid patients, track their progress, and send notifications tailored to their health is advancing greatly thanks to conversational AI. Some of these initiatives may conduct whole visits from the patients' homes, and by assessing the symptoms and examining the information provided by the patient, they can then direct the patient toward treatment or specialized appointments.

Using sophisticated deep learning frameworks and large-scale data analyses, AI is changing the healthcare industry.

Next Steps

So far we got to know what is the role of AI in healthcare. It’s time to Master Artificial Intelligence. For that you can visit Simplilearn's  Artificial Intelligence Engineer Course.If you are interested in learning more you can catch up on many Simplilearn’s courses that will help you to Master in Artificial Intelligence. 

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About the Author

Ravikiran A SRavikiran A S

Ravikiran A S works with Simplilearn as a Research Analyst. He an enthusiastic geek always in the hunt to learn the latest technologies. He is proficient with Java Programming Language, Big Data, and powerful Big Data Frameworks like Apache Hadoop and Apache Spark.

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