Deep Learning in Drug Discovery and Diagnostics (2017-2035) - By 2035, Deep Learning Solutions Can Result in Annual Savings of Over $35 Billion in the Diagnostics Segment Alone - Research and Markets

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Mar 24, 2017, 10:00 ET

DUBLIN, Mar 24, 2017 /PRNewswire/ --

Research and Markets has announced the addition of the "Deep Learning in Drug Discovery and Diagnostics, 2017 - 2035" report to their offering.

The Deep Learning: Drug Discovery and Diagnostics Market, 2017-2035 report examines the current landscape and future outlook of the growing market of deep learning solutions within the healthcare domain. Primarily driven by the big data revolution, deep learning algorithms have emerged as a novel solution to generate relevant insights from medical data.

Companies, such as Google, Amazon, Facebook, LinkedIn, IBM and Netflix, are already using deep learning algorithms to analyze users' activities and make customized suggestions and recommendations based on individual preferences. Today, in many ways, deep learning algorithms have enabled computers to see, read and write. In light of recent advances, the error rate associated with machines being able to analyze and interpret medical images has come down to 6%, which, some research groups claim, is even better than humans.

The likely benefits associated with the use of deep learning based solutions in the above mentioned areas is estimated to be worth multi billion dollars. There are well-known references where deep learning models have accelerated the drug discovery process and provided solutions to precision medicine. With potential applications in drug re-purposing and preclinical research, deep learning in drug discovery is likely to have great opportunity. In diagnostics, an increase in the speed of diagnosis is likely to have a profound impact in regions with large patient to physician ratios. The implementation of such solutions is anticipated to increase the efficiency of physicians providing a certain amount of relief to the overly-burdened global healthcare system.

Companies Mentioned

CRG
CureMetrix
Facebook
Fidelity Management & Research
Finance Wales
Finnish Funding Agency for Innovation
First Round Capital
Fitbit
Flatiron Health
Flipkart
GE Ventures
Google
GSK
Medtronic
MedyMatch Technology
Merck
Merge Healthcare
Metabolon
Methinks Software
Microsoft
(300+ Others)

Key Topics Covered:

1. PREFACE

2. EXECUTIVE SUMMARY

3. INTRODUCTION

4. MARKET OVERVIEW

5. COMPANY PROFILES

6. CASE STUDY: IBM WATSON VERSUS GOOGLE DEEPMIND

7. CAPITAL INVESTMENTS AND FUNDING

8. OPPORTUNITY ANALYSIS

9. COMPANY VALUATION ANALYSIS

10. DEEP LEARNING IN HEALTHCARE: EXPERT INSIGHTS

11. CONCLUSION

For more information about this report visit http://www.researchandmarkets.com/research/2svrc3/deep_learning_in

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SOURCE Research and Markets