How AI is transforming healthcare - from diagnosis to treatment

What is artificial intelligence?

It is a branch of computer science that understands and builds intelligent entities and software programs that mimic human brains. From chronic diseases and cancer to radiology and risk assessment, there are endless opportunities to leverage technology to implement more precise, efficient, and impactful interventions at the right moment to aid a patient's care. That is where AI comes in.

Artificial intelligence has immense capability to transform healthcare globally. Artificial intelligence (AI) and related technologies are increasingly prevalent in business and society and will be applied to healthcare.

International enterprises adopt AI models to enhance operational efficiencies, increase business outcomes and deliver superior customer quality and experiences.

Applications of AI are expanding into areas that were previously thought to be only the province of human experts with the help of digitized data acquisition, machine learning and computing infrastructure.

Recent applications of AI in healthcare

Artificial Intelligence is gradually changing the landscape of healthcare and biomedical research. Drug research and discovery is one of the more recent applications for AI in healthcare. A healthier behavior in individuals is encouraged with the new technology applications and apps that help in proactive management of a healthy lifestyle.

• Detection

AI is used to accurately detect severe or fatal diseases at a very early stage, such as cancer. According to the American Cancer Society, a high count of mammograms presents false results, leading to the wrong diagnosis of healthy women with cancer. The application of AI in healthcare has enabled 30 times faster translation of mammograms with 99% accuracy, eliminating the need for unnecessary biopsies.

More than 90 million people worldwide have diabetic retinopathy, which is a leading cause of blindness in adults. Fundus photography is an effective method to monitor the extent of diabetic retinopathy and to identify patients who will benefit from early treatments.

Ophthalmologists and computer scientists from the Aravind Eye Care System in India are working together to examine and deploy an automated image classification system to screen millions of retinal photographs of diabetic patients.

Advanced applications of AI, such as artificial neural networks, have enabled rapid, human-like interpretation of the ECG that detects the signals and patterns with precision, making the ECG a robust, non-invasive biomarker.

AI is also being used to detect early-stage heart disease, enabling doctors to monitor and detect potentially life-threatening episodes at earlier and more treatable stages.

• Diagnosis

Google's DeepMind Health technology has grown to deal with some complex healthcare issues over the last few years. It combines machine learning and systems neuroscience to build powerful general-purpose learning algorithms into neural networks that mimic the human brain.

Incomplete medical histories and large caseloads can lead to wrong and inefficient treatment plans. Using algorithms and deep learning, an AI model is introduced to diagnose breast cancer higher than 11 pathologists.

Beth Israel Deaconess Medical Center uses artificial intelligence to diagnose potentially deadly blood diseases at a very early stage. AI-enhanced microscopes are being used to scan for harmful bacterias (like E. coli and staphylococcus) in blood samples faster than manual scanning.

Zebra Medical Vision is using patient imaging data already available to the healthcare system. It highlights early and previously undetected signs of common chronic diseases.

This helps the radiologists with imaging scans that automatically analyze them for various clinical findings, and these reports are considered for decision making.

AI-assisted ECG findings

• Treatment plan

AI helps clinicians with a more comprehensive approach to disease management. It helps prepare improved, coordinated care plans and helps patients better manage and comply with their long-term treatment programs.

AI has introduced machines as Robots that range from simple laboratory robots to highly complex surgical robots. These machines can aid a human surgeon or execute operations by themselves. In addition to surgery, they are also used in hospitals and labs to assist in repetitive tasks, rehabilitation care, physical therapy, and support those suffering from long-term chronic conditions.

Advancements in AI have introduced robots to go even further and have 'conversations' and other social interactions with people to keep aging minds sharp.


AI in Healthcare | MediMagic

• Research

A drug life cycle lasts for an average of 12 years from the research lab to the patient, and only five in 5,000 of the drugs begin preclinical testing, and just one of these five is ever approved for human usage. Also, the research costs about $2.6 billion for each drug to go through clinical trials, and only 10% of those drugs are successfully brought to market. 

Latest advances in AI have streamlined the drug discovery and drug repurposing processes. 

BioXcel Therapeutics' work in AI-based drug development was named one of the "Most Innovative Healthcare AI Developments of 2019."

• Decision making

Predictive analytics can support clinical decision-making and prioritize administrative tasks by using pattern recognition to identify patients at risk of developing a condition.

AI in Medical | MediMagic

An electronic medical record is the systematized collection of patient data electronically-stored health information in a digital format. These records can be used and shared across different health care settings.

Another area where AI is beginning to take hold is healthcare lifestyle, environmental, genomic, or other factors influencing the patient's health.


The AI sector was valued at about $600 million in 2014 and is projected to reach $150 billion by 2026 in one of the world's highest-growth industries.

In 2020, the software solutions segment dominated the market for AI in healthcare and accounted for the largest revenue share of 40.6%. An increase in AI software solutions among healthcare payers and providers is one of the key factors driving the AI software segment.

AI has countless applications in healthcare. Whether it is being used to discover links between genetic codes, power surgical robots, or maximize hospital efficiency, AI has been a boon to the healthcare industry.

Innovations in AI healthcare technology stream the patient experience, helping hospital staff process millions, if not billions of data points, faster and more efficiently.

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