CMI, has recently added a concise research on the Transportation Predictive Analytics and Simulation Market to depict valuable insights related to significant market trends driving the industry. The report features analysis based on key opportunities and challenges confronted by market leaders while highlighting their competitive setting and corporate strategies for the estimated timeline.

Analysis tools such as SWOT analysis and Porter's five force model have been inculcated in order to present a perfect in-depth knowledge about Transportation Predictive Analytics and Simulation Market. tables, charts are added to help have an accurate understanding of this Transportation Predictive Analytics and Simulation Market.

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The number of vehicles around the world has been increased significantly in the recent past. This mainly due to significant growth in transportation infrastructure. According to GOV.UK, 2019, all motor traffic increased by 0.8% from 2018. Increasing population in cities is exerting pressure on road networks, leading to overcrowded road networks, lack of safe public transportation modes, poor traffic management, parking issues, road safety concerns, and poor road conditions. Predictive analytics and simulation software for transportation collects the data from sensors embedded in vehicles and process it to produce meaningful insights. This analysis can help to manage the road traffic flow efficiently and reduce congestions on the roads.

Market Overview:

Healthcare predictive analytics is generally used in the analysis of current data in order to predict future by using statistics, data mining, modeling, machine learning, and artificial intelligence. Increasing efficiency in the healthcare sector, the rising demand to curtail healthcare cost, and the advent of evidence-based and personalized medicine are some of the primary growth stimulants of the healthcare predictive analytics market. Rising importance of healthcare, especially in emerging nations is likely to generate new growth opportunities for the market in the foreseeable future.

Developing economies across the world are facing issues owing to the increasing medication cost. Governments are thus taking efforts to offer cost-effective services to the consumers at better quality. These efforts are likely to stimulate the predictive analytics market in the healthcare industry. The soaring demand for personalization for patient care, advancing technology, and rising awareness created by the top players are considered to encourage the market growth to a large extent.The global Healthcare Predictive Analytics Market is expected to exhibit a strong 29.3% CAGR over the forecast period (2018 to 2023), according to the latest research report from Market Research Future (MRFR).

Growing use of data-driven clinical decision support systems in the healthcare sector is likely to be a major driver for the global healthcare predictive analytics market over the forecast period. Clinical decision support systems are being welcomed in the healthcare sector around the world, as they provide the physician with a second layer of security, allowing more accurate diagnoses and better rehabilitation. Increasing applications of healthcare predictive analytics in population health management is also likely to be a major driver for the global healthcare predictive analytics market over the forecast period.

Competitive Analysis:

• IBM
• Verisk Analytics Inc.
• Cerner Corporation
• McKesson Corporation
• Oracle
• SAS
• Allscripts
• MedeAnalytics Inc
• Optum Inc
• Inovalon
• SCIO Health Analytics
• Health Catalyst
• Verscend Technologies Inc.
• Wipro Limited
• CitiusTech Inc

Segmentation:

The global healthcare predictive analytics market report is segmented on the basis of application, end use, and component.

By application, the global healthcare predictive analytics market is segmented into operations management, financial, population health management, and clinical. The operations management segment is further sub-segmented into demand forecasting, workforce planning and scheduling, inpatient scheduling, and outpatient scheduling. The financial segment is further classified as revenue cycle management, fraud detection, and others. The population health segment is further sub-segmented as population risk management, patient engagement, population therapy management, and other applications. The clinical segment includes quality benchmarking, patient care enhancement, and clinical outcome analysis and management.

By end use, the global healthcare predictive analytics market is segmented into payers, providers, and others.

By component, the global healthcare predictive analytics market is segmented into services, software, and hardware.

Regional Analysis:

Healthcare predictive analytics is generally used in the analysis of current data in order to predict future by using statistics, data mining, modeling, machine learning, and artificial intelligence. Increasing efficiency in the healthcare sector, the rising demand to curtail healthcare cost, and the advent of evidence-based and personalized medicine are some of the primary growth stimulants of the healthcare predictive analytics market. Rising importance of healthcare, especially in emerging nations is likely to generate new growth opportunities for the market in the foreseeable future.

Developing economies across the world are facing issues owing to the increasing medication cost. Governments are thus taking efforts to offer cost-effective services to the consumers at better quality. These efforts are likely to stimulate the predictive analytics market in the healthcare industry. The soaring demand for personalization for patient care, advancing technology, and rising awareness created by the top players are considered to encourage the market growth to a large extent.