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How Artificial Intelligence Can Improve Medical Treatments

Swati Tamhankar / 3 min read.
November 6, 2018
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Today’s technology is driven by a dictum, everything that can be automated will be automated and artificial intelligence (AI) is the unstoppable technology in the automation sector. After conquering the field of robotics, AI has entered the healthcare sector to improve diagnosis and medical treatments.

The concept of AI has been around since 1956, but it has made significant developments in the medical field in the last 10 years. AI in medicine has become the most sought-after technology for researchers, startups, entrepreneurs, and especially tech giants including Google. According to the research firm, Allied Market Research, the AI in medicine market was valued at $719 million in 2017 and is expected to reach $18,119 million at the end of 2025, registering a CAGR of 49.6% in the period from 2017 to 2025. The statistics and the incorporation of AI variants such as deep learning and machine learning showed that AI is the most useful thing happened in the medical field. The best way to understand the impact of AI in medicine is to break down the applications into three major parts: medical practice, algorithmic solutions, and visual tools.

AI in Everyday Medical Practice

AI has the potential to eradicate the enigma of diagnostics and eliminate the unnecessary deaths in clinics and hospitals. Natural language processing is a branch of AI that can help computers understand human writing and speech. It can scan and review thousands of medical records and evaluate the best steps to cure a patient with multiple ailments. Moreover, AI can watch and learn from doctors at work.

In San Francisco, a startup named Forward is using AI to explore how machines learn from observing doctors. Instead of analyzing the data generated by doctors, the machine can follow their procedures step-by-step. Forward’s AI records and analyzes how specialists achieve the superior outcome and the results help patients get a faster treatment.


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Algorithmic Solutions

The most commonly used AI-based applications are algorithmic. With the help of consensus algorithms and the data entered by physicists and specialists such as patient’s age, genetics, history of any diseases, habits, or any medical-associated problems, an AI can review dozens of data and suggest an appropriate combination of medicines. An AI application developed by Permanente Medical Group, a healthcare service provider in Northern California, uses data compiled from 650,000 hospital patients to analyze which patients need intensive care. Moreover, the AI-based system can alert doctors regarding at-risk patients, so they can get necessary treatments before they end up in ICU.

AI-Based Visual Tools

The failure of the human eye to detect a slight anomaly can be rectified with the help of AI. The survey states that at least 34% of the time, two or more radiologists studying the same mammography offer different medical opinion and thus treatment. On the other hand, visual recognition software powered by AI can use the same technique used by specialists to diagnose a disease 5% more accurately than an average physician. The tool can scan thousands of clinical images and compare them to offer an accurate and quick diagnosis. Moreover, experts believe the accuracy gap between human and digital eye is expected to widen as AI and machine learning is advancing at a rapid pace.

Even though people fear that AI will take over the jobs of doctors in future, several experts believe that such opinion is just a hype and based on science-fiction than reality. AI offers unlimited opportunities in the medical field and has the potential to upgrade the healthcare system far beyond its today’s capabilities.

Categories: Artificial Intelligence, Robotics
Tags: Artificial Intelligence, blog, healthcare, medicine

About Swati Tamhankar

Swamini Kulkarni holds a bachelor's degree in engineering and works as a content writer. She is deeply fascinated by technological advancements and the trending topic in the world. When she is not glued to the computer, she loves to read, travel, and spend time thinking about how she could read and travel more often.

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