The report "Global Machine Learning in Medical Imaging Market" intends to provide innovative market intelligence and help decision makers take comprehensive investment evaluation. Also identifies and analyses the emerging trends along with major drivers, challenges, opportunities and entry strategies for various companies in the global Machine Learning in Medical Imaging Industry.
Pune, India -- (SBWIRE) -- 06/25/2020 -- Machine Learning in Medical Imaging Market was valued at significant market size, growing with a CAGR surpassing 38% in the forecast period. Medical imaging is a process in which diagnostic procedures involving the creation and monitoring of visual aids and image representations of the human body performance and function. The way diagnostics are performed and the whole procedure changes with the integration of artificial intelligence (AI), into health and medical imaging.
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The AI allows surgeons to complete the collection of images and how to identify these images for individual and patient conclusion and personalized care. Artificial intelligence consists mainly of two different types, robots and learning machines. Widespread availability and ability of personalized treatment, improved procedures and treatment of the patients are also expected to drive the market growth. Increasing count of diagnostic procedures will drive demand for machine learning in medical imaging market. High cost and reluctance of adoption of these systems is anticipated to restrain the market.
As per latest research studies, there have been strong improvements on the use of AI in various imaging methods and therapeutic fields. One of the examples revealed that machine learning is capable of distinguishing and differentiating between four different chest x-radiation diseases such as lung malignancy, primary lung cancer, metastasized, pulmonary active tuberculosis, pneumonia and pneumothorax. Machine learning allows doctors, surgeons and radiologists to classify and prioritize patients in the most severe or difficult conditions. Large, established healthcare companies are heavily investing in machine learning based medical imaging, majorly through strategic partnerships, merger and acquisitions. In 2018, Samsung Electronics exhibited artificial intelligence products which can detect breast cancers, lung nodules using chest x-rays.
Brief about Machine Learning in Medical Imaging Market Report with TOC@ https://www.arcognizance.com/report/machine-learning-in-medical-imaging-market-global-industry-analysis-size-share-trends-and-forecast-2015-2025
Machine learning can also significantly improve the image clarity and interpretation of MRIs in cases of arthritis and bone issues. Similarly, Siemens has recently introduced intelligence solutions which measures potential abnormalities o certain diseases. Furthermore, GE Healthcare has also formed a partnership with Intel to utilize ML for a wide range of medical imaging applications. Increasing diagnosis of coronary calcification, osteoporosis, lung emphysema, and fatty liver will further force upon utilization of machine learning for early detection and knowledge of risk level in patients. North America and Europe offer potential opportunities for the growth of the global market since these are developed regions with advanced healthcare infrastructure.
Global Machine Learning in medical imaging market is segmented on the basis of product, application and geography. Based on the Product, the global market is categorized into hardware, software and services. On the basis of application, the market is categorized into hospitals, clinics, diagnostic centers and others. Geographically, the market is divided into Asia-Pacific, North America, Europe, Latin America and (MEA).
The key players operating within the global Machine Learning in Medical Imaging Market include Clarify Health Solutions, Voxel Technology, IDx Technologies Inc., Medopad Ltd., Prognos, BenevolentAI, Babylon, Freenome Inc. OrCam, Ada Health GmbH, Zebra Medical Vision Inc., BioXcel Therapeutics, Qventus Inc, K Health, GNS Healthcare, mPulse Mobile, Viz.ai Inc., Renalytix AI plc, Beijing Pushing Technology Co. Ltd., PAIGE.
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Some Points From TOC:
Chapter One: Market Introduction
Chapter Two: Executive Summary
Chapter Three: Global Machine Learning in Medical Imaging Market – Key Product Dynamics
3.1. Key Market Drivers
3.2. Key Market Restraints
3.3. Market Opportunities
3.4. Future Trends
3.5. Impact Analysis of Drivers and Restraints
Chapter Four: Global Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025 – By Product
Chapter Five: Global Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025 – By Application
5.3. Diagnostic Centers
Chapter Six: Global Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025 – By Region
6.1. North America
6.4. Latin America
6.5. Middle East & Africa
Chapter Seven: North America Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025
7.1. North America Machine Learning in Medical Imaging Market – By Product, 2015-2025
7.2. North America Machine Learning in Medical Imaging Market – By Application, 2015-2025
7.2.3. Diagnostic Centers
7.3. North America Machine Learning in Medical Imaging Market – By Country, 2015-2025
Chapter Eight: Europe Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025
8.1. Europe Machine Learning in Medical Imaging Market – By Product, 2015-2025
8.2. Europe Machine Learning in Medical Imaging Market – By Application, 2015-2025
8.2.3. Diagnostic Centers
8.3. Europe Machine Learning in Medical Imaging Market – By Country, 2015-2025
8.3.6. Rest of Europe
Chapter Nine: Asia-Pacific Machine Learning in Medical Imaging Market – Analysis and Revenue Forecast, 2015-2025
9.1. Asia Pacific Machine Learning in Medical Imaging Market – By Product, 2015-2025
9.2. Asia Pacific Machine Learning in Medical Imaging Market – By Application, 2015-2025
9.2.3. Diagnostic Centers
9.3. Asia-Pacific Machine Learning in Medical Imaging Market – By Country, 2015-2025
9.3.4. South Korea
9.3.5. Rest of Asia-Pacific
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