Global Deep Learning Market in Drug Discovery and Diagnostics Market Report 2023: Players Include Aegicare, Aiforia Technologies, Ardigen, Berg and Google – ResearchAndMarkets.com

DUBLIN–(BUSINESS WIRE)–The “Deep Learning Market in Drug Discovery and Diagnostics: Distribution by Therapeutic Areas and Key Geographical Regions: Industry Trends and Global Forecasts (2nd Edition), 2023-2035” report has been added to ResearchAndMarkets.com’s offering.

This report features an extensive study of the current market landscape and the likely future potential of the deep learning solutions market within the healthcare domain. The report highlights the efforts of several stakeholders engaged in this rapidly emerging segment of the pharmaceutical industry. The report answers many key questions related to this domain.

Since the mid-twentieth century, computing devices have continually been explored for applications beyond mere calculations, to emerge as machines that possess intelligence. These targeted efforts have contributed to the introduction of artificial intelligence, the next-generation simulator that employs programmed machines possessing the ability to comprehend data and execute the instructed tasks.

The progress of artificial intelligence can be attributed to machine learning, a field of study imparting computers with the ability to think without being explicitly programmed. Deep learning is a complex machine learning algorithm that uses a neural network of interconnected nodes / neurons in a multi-layered structure, thereby enabling the interpretation of large volumes of unstructured data to generate valuable insights. The mechanism of this technique resembles the interpretation ability of human beings, making it a promising approach for big data analysis.

Owing to the distinct characteristic of deep learning algorithm to imitate human brain, it is currently being deployed in the life sciences domain, primarily for the purpose of drug discovery and diagnostics. Considering the challenges associated with drug discovery and development, such as the high attrition rate and increased financial burden, deep learning has been found to improve the overall R&D productivity and enhance diagnosis / prediction accuracy.

Recent advancements in the deep learning domain have demonstrated its potential in other healthcare-associated segments, such as medical image analysis, molecular profiling, virtual screening and sequencing data analysis. Driven by the ongoing pace of innovation and the profound impact of implementation of such solutions, deep learning is anticipated to witness substantial growth in the foreseen future.

Company Profiles

• Aegicare
• Aiforia Technologies
• Ardigen
• Berg
• Google
• Huawei
• Merative
• Nference
• Nvidia
• Owkin
• Phenomic AI
• Pixel AI

Key Market Insights

What is the Current Market Landscape of the Deep Learning Market Focused on Drug Discovery and Diagnostics?

Currently, more than 200 industry players are focused on providing deep learning-based services / technologies for drug discovery and diagnostic purposes. The primary focus areas of these companies include big data analysis, medical imaging, medical diagnosis and genetic / molecular data analysis.

What is the Market Size of Deep Learning in Drug Discovery?

Lately, the industry has witnessed the development of advanced deep learning technologies / software. These technologies possess the ability to obviate the concerns associated with the conventional drug discovery process. Eventually, such technologies will aid in the reduction of financial burden associated with drug discovery.

The global deep learning market focusing on drug discovery is anticipated to grow at a CAGR of over 20% between 2023 and 2035. By 2035, the deep learning in drug discovery market for oncological disorders is expected to capture the majority share. In terms of geography, the market in North America and Europe is anticipated to grow at a relatively faster pace by 2035.

What is the Market Size of Deep Learning in Diagnostics Market?

The adoption of deep learning-powered technologies to assist medical diagnosis, as well as prevention of diseases, has increased in the recent past. The global deep learning market focusing on diagnostics is anticipated to grow at a CAGR of over 15% between 2023 and 2035. By 2035, the deep learning in diagnostics market in North America is expected to capture the majority share. In terms of therapeutic areas, the deep learning in diagnostics market for endocrine and respiratory disorders is anticipated to grow at a relatively faster pace by 2035.

Which Segment held the Largest Share in Deep Learning Market?

The study covers the revenues from deep learning technology for their potential applications in the drug discovery and diagnostics domain. As of 2022, deep learning based diagnostics held the largest share of the market, owing to the efficiency and precision of applying deep learning-powered diagnostic solutions.

What are the Key Advantages offered by Deep Learning in Drug Discovery and Diagnostics?

The use of deep learning in drug discovery has the potential to reduce capital requirements and the failure-to-success ratio, as algorithms are better equipped to analyze large datasets. Similarly, in diagnostics domain, deep learning technology can be used to assist medical professionals in medical imaging and interpretation. This enables quick and efficient diagnosis of disease indications at an early stage.

What are the Key Drivers of Deep Learning in Drug Discovery and Diagnostics Market?

In the last decade, the healthcare industry has witnessed an inclination towards the adoption of information services and digital analytical solutions.

This can be attributed to the fact that companies have recently shifted towards high-resolution medical images and electronic health and medical records, generating large and complex data, referred to as big data. In order to analyze such large, structured and unstructured datasets, efficient tools and technology, such as deep learning, are required.

For more information about this report visit https://www.researchandmarkets.com/r/cpyj6l

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