Healtcare Deep Learning in Drug Discovery and Diagnostics Ma
Deep Learning in Drug Discovery and Diagnostics Market - Global
Industry Insights, Trends, Outlook, and Opportunity Analysis, 2016-2024
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).
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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 portfolio.