LONDON--(BUSINESS WIRE)--Quantzig, a global analytics solutions provider, has announced the completion of their latest article on the top benefits of machine learning in the healthcare industry.
Patient outcomes have now taken the place from products and services as the main focus of healthcare providers. Medical organizations are pressing down on this trend and are now implementing advanced technologies like machine learning in healthcare to progress patient care and patient outcomes. As a result, the use of machine learning in healthcare is gradually but increasingly revolutionizing the healthcare industry.
Request a proposal to know more about the top benefits of machine learning in the healthcare industry.
While the ability to record massive amounts of information about individual patients is transforming the healthcare industry, the volume of data being gathered is impossible for human beings to evaluate. Machine learning offers a way to automatically find patterns and examine unstructured data. This allows healthcare professionals to move to a personalized care system, which is known as precision medicine.
According to the analytics experts at Quantzig, “Machine learning technology plays a key role in diagnosing diseases and other medical issues, which is one of the major healthcare industry challenges.”
Request a demo to know more about the scope of our research.
Top benefits of machine learning in the healthcare industry
- Medical imaging: Due to advanced technologies like machine learning and deep learning, computer visions have now become one of the most extraordinary breakthroughs in the healthcare industry. Major companies in the medical industry are trying to combine cognitive computing with genomic tumor sequencing to help develop advanced precision medicines. Also, by implementing machine learning in healthcare, it is possible to find diabetic retinopathy and macular edema in the photographs of the retinal fundus.
- Robotic surgery: In recent times, robotic surgery has been attaining massive popularity. Machine learning technologies help in the use of robots for surgical procedures in the healthcare industry. Substituting human surgeons with robots will have numerous benefits like operations in tighter spaces, with finer detail, and radically reducing the chances for human-based challenges such as shaking hands. Machine learning in robotic surgery mostly focusses around machine vision and is used to evaluate distances to a much higher degree of accurateness or identifying specific parts or organs within the body. Get in touch to know more about the top benefits of machine learning in the healthcare industry.
- Creating electronic smart records: At present, there a plethora of patient data in the healthcare industry. This has made it crucial for organizations in the healthcare industry to use smart electronic healthcare records. The applications of machine learning in the development of electronic smart records include using records with inbuilt artificial intelligence or machine learning so as to help with keeping medical records, understanding health conditions, and suggesting treatment plans.
- Visit our page, to view a comprehensive list of the top benefits of machine learning in the healthcare industry.
Quantzig is a pure-play analytics advisory firm concentrated on leveraging analytics for prudent decision making and offering solutions to clients across several industrial sectors.
Request a proposal to see how Quantzig’s solutions can help you.
View the complete list of the top benefits of machine learning in the healthcare industry:
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on all of Quantzig’s services and the solutions they have provided to Fortune 500 clients across all industries, please contact us.