The healthcare industry has quickly absorbed the digitization trends, and is increasingly incorporating technology for patient treatment, case handling, financial management and security management, amongst others. Lately, the advancement in Artificial Intelligence (AI) technology is drastically helping in the faster case resolution in the healthcare industry. AI-based systems are being increasingly developed by companies such as Siemens and Philips. AI is the simulation of human-like intelligence in computing systems through a set of self-learning algorithms which makes the AI think and act like a human being. AI algorithms are capable of using historic data for predicting future outcomes. Data-driven treatments can be implemented through the use of AI. For instance, a patient's blood pressure record over the years can be monitored to suggest the ideal treatment course for the individual, and the patient can be asked to avoid certain actions that cause blood pressure spikes in the future. The combination of AI and data analytics has the power to reduce diagnostic errors and optimize medicine doses in the healthcare industry. Furthermore, the detection of cancer can also be facilitated with AI. Researchers at Google AI Healthcare, for instance, created an algorithm called Lymph Node Assistant (LYNA), which was trained to analyze histology slides for the detection of metastatic breast cancer tumors from the biopsies of lymph nodes. The algorithm was able to classify a sample as non-cancerous or cancerous with an accuracy of 99%. Also, the incorporation of AI in medical devices is also on the rise. SmartExam system by Koninklijke Philips N.V., for instance, helps in the automation of MR exam planning, scanning and processing with ease. The AI software used in SmartExam automatically plans scanning geometries based on the preference of the medical professional. California-based Caption Health, on the other hand, provides an AI software that enables the healthcare providers to interpret ultrasound data at a faster rate. It provides real-time guidance on the positioning and manipulation of the transducer on the patient's body, thereby aiding the ultrasound technician to produce results faster. Thus, the power of AI for faster resolution of patient cases in the healthcare industry, coupled with its predictive forecasting features is helping in the growth of the global artificial intelligence in medicine market.
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The COVID-19 pandemic has severely impacted the lives of both businesses and individuals alike. The healthcare industry has been burdened with the rise of COVID-19 cases in countries like Brazil, USA and India, amongst others. Public health organizations are relying on AI technology for curbing the spread of the Coronavirus. Patient data can be used to analyze the presence of COVID-19 hotspots, which makes it easier to isolate individuals. Furthermore, AI algorithms also help in predicting the increase of COVID-19 patients in the future, based on historical data. Also, AI-based models have been successful in drug discovery in the previous years, and these models are also being used for the development of a COVID-19 vaccine by pharmaceutical companies. Graph Convolutional Neural Networks (GCNN) are being increasingly used for this purpose. Therefore, the COVID-19 pandemic is expected to have a positive impact on the global artificial intelligence in medicine market.
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The detailed research study provides qualitative and quantitative analysis of the global artificial intelligence in medicine market. The artificial intelligence in medicine market has been analyzed from demand as well as supply side. The demand side analysis covers market revenue across regions and further across all the major countries. The supply side analysis covers the major market players and their regional and global presence and strategies. The geographical analysis done emphasizes on each of the major countries across North America, Europe, Asia Pacific, Middle East & Africa and Latin America
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Global Artificial Intelligence in Medicine Market
- By Component
- Hardware
- Software
- Service
- By Technology
- Querying Method
- Natural Language Processing
- Context Aware Processing
- Speech Recognition
- Decision Management
- Others (Biometrics, AI Modeling, Etc.)
- By Application
- Robot assisted Surgery
- Virtual Nursing Assistants
- Administrative Workflow Assistance
- Fraud Detection, Connected Machines
- Clinical Trails
- Preliminary Diagnosis
- Others (Dosage Error Reduction, Cybersecurity, Etc.)
- By End Users
- Healthcare Providers
- Pharmaceutical & Biotechnology Company
- Patient
- Payer
- By Region:
- North America
- U.S.
- Canada
- Mexico
- Rest of North America
- Europe
- France
- The UK
- Spain
- Germany
- Italy
- Nordic Countries
- Denmark
- Finland
- Iceland
- Sweden
- Norway
- Benelux Union
- Belgium
- The Netherlands
- Luxembourg
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- New Zealand
- Australia
- South Korea
- Southeast Asia
- Indonesia
- Thailand
- Malaysia
- Singapore
- Rest of Southeast Asia
- Rest of Asia Pacific
- Middle East & Africa
- Saudi Arabia
- UAE
- Egypt
- Kuwait
- South Africa
- Rest of Middle East & Africa
- Latin America
- Brazil
- Argentina
- Rest of Latin America
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