Deep Learning in Drug Discovery and Diagnostics Market Explore Future Growth 2018-2026 Predicted by Global Top Players
Deep learning is machine learning that analyzes large volumes of labeled and unlabeled data along with multi-dimensional and complex data with non-trivial patterns. It is touted to be a replacement for manual feature engineering with unsupervised feature learning. Massive influx of multimodality data in recent times further necessitates use of artificial intelligence for data analytics in health information systems. This in turn has impelled rise in deployment of analytical data-driven models generation, which are based on machine learning in health informatics. This is expected to be one of the vital factors supporting growth of deep learning in drug discovery and diagnostics market in the near future. Deep learning in drug discovery and diagnostics market is an upcoming technique deeply rooted in artificial neural networks and is expected to gain traction in the near future. It is expected to evolve as an important tool deep learning about the healthcare information system and would be utilized to restructure the future of healthcare sector and artificial intelligence. Rapid developments in computer-based operations and efficient and quick data storage are also contributing to fast uptake of the technology. The technique automatically generates optimum high level features with semantic effective input data interpretation, which is expected to support growth of deep learning in drug discovery and diagnostics market over the forecast period (2016–2024).
The provision of reducing time interval in drug discovery is expected to underpin the growth of deep learning in drug discovery and diagnostics market:
Conventionally, drug discovery and drug development was considered to be a complex and time consuming process. Various analytical approaches are being used to further usher in developments. Latest methods such as data mining, homology modeling, conventional machine learning and its biologically inspired branch technique, deep learning are the sources for next-generation drug discovery methods. The abovementioned reason is projected to fuel growth rate of deep learning in drug discovery and diagnostics market. Furthermore, healthcare and life sciences organizations are leveraging artificial intelligence and deep learning approach to enhance their product
Google Inc., IBM Corp., Microsoft Corporation, Qualcomm Technologies, Inc., General Vision Inc., Insilico Medicine, Inc., NVIDIA Corporation, Zebra Medical Vision, Inc., Enlitic, Ginger.io, MedAware Lumiata.
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