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HBR recently published findings of a study that involved orthopedic patients; it was found that AI-assisted operations reduced surgery complications by five times as compared to surgeons operating alone. Yes, there is such a thing as virtual nursing.
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Not only can machine language-powered nursing chatbots and robots interact with patients more regularly than human nurses, but also can serve as intelligent gatekeepers of information between patients and doctors. By avoiding regular hospital visits, and providing proper care between mandatory visits, these virtual nurses can reduce the recovery time, and mitigate the stress of medical care.
- Deep Learning in Medicine | NVIDIA.
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Medical care is complex; even the most trivial of hospital visits triggers dozens of separate workflows, involving doctors, nurses, chemists, attendants, facilities managers, and more. Watson helps doctors by analyzing thousands of medical research papers using its natural language processing capabilities, helping them devise effective treatment plans.
Personalized medical care is a bit of a luxury, reserved for those who can afford it. The application of predictive analysis in disease assessment and management hardly requires any underscoring. Called supervised learning, this approach enabled physicians and doctors to select the right diagnosis from a limited original set of possibilities, based on the genetic information of the patient.
Machine Learning Is Taking Over the Medical Profession — But Not in the Way You Might Think
Machine learning is a major enabler here, as it can help doctors draw insights from the entire medical history of the patient, including generic attributes. Sophisticated health measurement devices and wearables that keep track of important health measures such as heart rate and blood pressure provide for another source of massive data that can make personalized treatments a reality, at scale, and across the world.
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AI-Based Precision Medicine Is Still In Its Early Stages
A Nature Research Journal. Focus 18 April Machine learning has had a significant impact in many areas of science and technology, including life science and medical research. In this Focus issue, we highlight the recent advances that have been made in the development of machine learning algorithms for fundamental aspects such as statistical bioinformatics to their deployment in clinical diagnosis, prognosis and drug development. Machine learning is swiftly infiltrating many areas within the healthcare industry, from diagnosis and prognosis to drug development and epidemiology, with significant potential to transform the medical landscape.
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Better medicine through machine learning: What’s real, and what’s artificial?
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Top 10 Applications of Machine Learning in Healthcare
May 19, Business intelligence and analytics. There is a certain level of stigma that exists around using machine learning and location data in business applications, understandably due to risks inherent in exploitation of individual privacy. May 20, Process automation. Apr 26, Feb 03, Automation and robotics. Feb 19, Machine Learning for Dermatology — 5 Current Applications.
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