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Global Markets for Machine Learning in the Life Sciences

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    Report

  • 136 Pages
  • September 2022
  • Region: Global
  • BCC Research
  • ID: 5654412
Description Jump to:

This report highlights the current and future market potential for machine learning in life sciences and provides a detailed analysis of the competitive environment, regulatory scenario, drivers, restraints, opportunities and trends in the market. The report also covers market projections from 2022 through 2027 and profiles key market players. The publisher analyzes each technology in detail, determines major players and current market status, and presents forecasts of growth over the next five years. Scientific challenges and advances, including the latest trends, are highlighted. Government regulations, major collaborations, recent patents and factors affecting the industry from a global perspective are examined.

Key machine learning in life sciences technologies and products are analyzed to determine present and future market status, and growth is forecast from 2022 to 2027. An in-depth discussion of strategic alliances, industry structures, competitive dynamics, patents and market driving forces is also provided.

Report Includes

  • 32 data tables and 28 additional tables
  • A comprehensive overview and up-to-date analysis of the global markets for machine learning in life sciences industry
  • Analyses of the global market trends, with historic market revenue data for 2020 and 2021, estimates for 2022, and projections of compound annual growth rates (CAGRs) through 2027
  • Highlights of the current and future market potential for ML in life sciences application, and areas of focus to forecast this market into various segments and sub-segments
  • Estimation of the actual market size for machine learning in life sciences in USD million values, and corresponding market share analysis based on solutions offering, mode of deployment, application, and geographic region
  • Updated information on key market drivers and opportunities, industry shifts and regulations, and other demographic factors that will influence this market demand in the coming years (2022-2027)
  • Discussion of the viable technology drivers through a holistic review of various platform technologies for new and existing applications of machine learning in the life sciences areas
  • Identification of the major stakeholders and analysis of the competitive landscape based on recent developments and segmental revenues
  • Emphasis on the major growth strategies adopted by leading players of the global machine learning in life sciences market, their product launches, key acquisitions, and competitive benchmarking
  • Profile descriptions of the leading market players, including Alteryx Inc., Canon Medical Systems Corp., Hewlett Packard Enterprise (HPE), KNIME AG, Microsoft Corp., and Phillips Healthcare

Table of Contents

Chapter 1 Introduction
1.1 Study Goals and Objectives
1.2 Reasons for Doing the Study
1.3 Intended Audience
1.4 Scope and Format
1.5 Methodology
1.6 Information Sources
1.7 Geographical Breakdown
1.8 Analyst's Credentials
1.9 Custom Research
1.10 Related Research Reports
Chapter 2 Summary and Highlights
Chapter 3 Market Overview
3.1 Introduction
3.1.1 Understanding Artificial Intelligence in Healthcare
3.1.2 Artificial Intelligence in Healthcare Evolution and Transition
Chapter 4 Impact of the Covid-19 Pandemic
4.1 Introduction
4.1.1 Impact of Covid-19 on the Market
Chapter 5 Market Dynamics
5.1 Market Drivers
5.1.1 Investment in Ai Health Sector
5.1.2 Rising Chronic Diseases
5.1.3 Advanced, Precise Results
5.1.4 Increasing Research and Development Budget
5.2 Market Restraints and Challenges
5.2.1 Reluctance Among Medical Practitioners to Adopt Ai-Based Technologies
5.2.2 Privacy and Security of User Data
5.2.3 Hackers and Machine Learning
5.2.4 Ambiguous Regulatory Guidelines for Medical Software
5.3 Market Opportunities
5.3.1 Untapped Potential in Emerging Markets
5.4 Value Chain Analysis
Chapter 6 Market Breakdown by Offering
6.1 Software
6.1.1 Market Size and Forecast
6.2 Services
6.2.1 Market Size and Forecast
Chapter 7 Market Breakdown by Deployment Mode
7.1 Cloud
7.1.1 Market Size and Forecast
7.2 On-Premises
7.2.1 Market Size and Forecast
Chapter 8 Market Breakdown by Application
8.1 Diagnosis
8.1.1 Market Size and Forecast
8.2 Therapy
8.2.1 Market Size and Forecast
8.3 Healthcare Management
8.3.1 Market Size and Forecast
Chapter 9 Market Breakdown by Region
9.1 Global Market
9.2 North America
9.2.1 U.S.
9.2.1 Canada
9.3 Europe
9.3.1 Germany
9.3.2 U.K.
9.3.3 France
9.3.4 Italy
9.3.5 Spain
9.3.6 Rest of Europe
9.4 Asia-Pacific
9.4.1 China
9.4.2 Japan
9.4.3 India
9.4.4 Rest of Asia-Pacific
9.5 Rest of the World
Chapter 10 Regulations and Finance
10.1 Regulatory Framework
10.1.1 American Diabetes Association's Standards of Medical Care in Diabetes
10.1.2 Ata Guidelines for Artificial Intelligence
10.1.3 Indian Ai Guidelines, Strategy, and Standards
Chapter 11 Competitive Landscape
11.1 Overview
11.1.1 Development
11.1.2 Cloud
11.1.3 Users
11.1.4 Parent Market: Global Artificial Intelligence Market
Chapter 12 Company Profiles
  • Alteryx Inc.
  • Anaconda, Inc.
  • Canon Medical Systems Corp.
  • Enlitic Inc.
  • Hewlett Packard Enterprise (Hpe)
  • Imagen Technologies
  • Ibm Corp.
  • Intel Corp.
  • Knime AG
  • Microsoft Corp.
  • Nvidia
  • Oracle Corp.
  • Philips Healthcare
  • Sas Institute Inc.
List of Tables
Summary Table: Global Market for Machine Learning in the Life Sciences, by Region, Through 2027
Table 1: Regional User Data Privacy Acts
Table 2: Cancer Statistics Across Major Asian Countries, by Cancer Site/Type, 2020
Table 3: Global Market for Machine Learning in the Life Sciences, by Offering, Through 2027
Table 4: Global Market for Software in Machine Learning in the Life Sciences, by Region, Through 2027
Table 5: Global Market for Services in Machine Learning in the Life Sciences, by Region, Through 2027
Table 6: Global Market for Machine Learning in the Life Sciences, by Deployment Mode, Through 2027
Table 7: Global Market for Cloud Deployment in Machine Learning in the Life Sciences, by Region, Through 2027
Table 8: Global Market for On-premise Deployment of Machine Learning in the Life Sciences, by Region, Through 2027
Table 9: Global Market for Machine Learning in the Life Sciences, by Application, Through 2027
Table 10: Global Market for Machine Learning in Diagnostic Applications, by Region, Through 2027
Table 11: Global Market for Machine Learning in Therapeutic Applications, by Region, Through 2027
Table 12: Global Market for Machine Learning in Healthcare Management Applications, by Region, Through 2027
Table 13: Global Market for Machine Learning in the Life Sciences, by Region, Through 2027
Table 14: North American Market for Machine Learning in the Life Sciences, by Offering, Through 2027
Table 15: North American Market for Machine Learning in the Life Sciences, by Deployment Mode, Through 2027
Table 16: North American Market for Machine Learning in the Life Sciences, by Application, Through 2027
Table 17: North American Market for Machine Learning in the Life Sciences, by Country, Through 2027
Table 18: European Market for Machine Learning in the Life Sciences, by Offering, Through 2027
Table 19: European Market for Machine Learning in the Life Sciences, by Deployment Mode, Through 2027
Table 20: European Market for Machine Learning in the Life Sciences, by Application, Through 2027
Table 21: European Market for Machine Learning in the Life Sciences, by Country, Through 2027
Table 22: Asia-Pacific Market for Machine Learning in the Life Sciences, by Offering, Through 2027
Table 23: Asia-Pacific Market for Machine Learning in the Life Sciences, by Deployment Mode, Through 2027
Table 24: Asia-Pacific Market for Machine Learning in the Life Sciences, by Application, Through 2027
Table 25: Asia-Pacific Market for Machine Learning in the Life Sciences, by Country, Through 2027
Table 26: Number of New Cancer Cases in Japan, by Cancer Type/Site, 2020
Table 27: Rest of the World Market for Machine Learning in the Life Sciences, by Offering, Through 2027
Table 28: Rest of the World Market for Machine Learning in the Life Sciences, by Deployment Mode, Through 2027
Table 29: Rest of the World Market for Machine Learning in the Life Sciences, by Application, Through 2027
Table 30: Regulations Pertaining to the Market for Machine Learning in the Life Sciences, by Select Countries
Table 31: Alteryx: Products and Services
Table 32: Alteryx: Recent Developments, 2020-2021
Table 33: Anaconda, Inc.: Products and Services
Table 34: Anaconda, Inc.: Recent Developments, 2021
Table 35: Canon Medical: Company Financials, 2019 and 2020
Table 36: Canon Medical: Product Portfolio
Table 37: Canon Medical: Strategies and Development, 2020-2021
Table 38: Enlitic Inc.: Product Portfolio
Table 39: HPE: Products and Services
Table 40: HPE: Recent Developments, 2020-2021
Table 41: Imagen: Product Portfolio
Table 42: IBM Corp.: Products and Services
Table 43: IBM Corp.: Recent Developments, 2020-2021
Table 44: Intel Corp.: Products and Services
Table 45: Intel Corp.: Recent Developments, 2020-2021
Table 46: Knime AG: Products and Services
Table 47: Knime AG: Recent Developments, 2020
Table 48: Microsoft Corp.: Products and Services
Table 49: Microsoft Corp.: Recent Developments, 2020-2021
Table 50: Nvidia: Company Financials, 2019 and 2020
Table 51: Nvidia: Product Portfolio
Table 52: Nvidia: Recent Development, 2020
Table 53: Oracle Corp.: Products and Services
Table 54: Oracle Corp.: Recent Developments, 2021
Table 55: Phillips Healthcare: Company Financials, 2019 and 2020
Table 56: Philips Healthcare: Product Portfolio
Table 57: Phillips Healthcare: Strategies and Development, 2020-2021
Table 58: SAS Institute, Inc.: Products and Services
Table 59: SAS Institute, Inc.: Recent Developments, 2020-2021

List of Figures
Summary Figure A: Global Market for Machine Learning in the Life Sciences, by Region, 2020-2027
Summary Figure B: Global Market Shares of Machine Learning in the Life Sciences, by Region, 2021
Figure 1: Global Funding in Health-Tech Companies, 2010-2019
Figure 2: Global Deaths Due to the Top Three Chronic Diseases, 2005-2030
Figure 3: Increased Incidence of Cancer, 2012 and 2030
Figure 4: Global Distribution of Deaths from Chronic Diseases, by Income Group, 2019
Figure 5: Machine Learning Enterprise Adoption
Figure 6: Rising Trends in Healthcare Spending, by Institution, 2015-2035
Figure 7: Value Chain Analysis of Machine Learning in the Life Sciences
Figure 8: Global Market Shares of Machine Learning in the Life Sciences, by Offering, 2021
Figure 9: Global Market for Machine Learning in the Life Sciences, by Offering, 2020-2027
Figure 10: Machine Learning Software
Figure 11: Global Market for Software in Machine Learning in the Life Sciences, 2020-2027
Figure 12: Global Services Market for Machine Learning in the Life Sciences, 2020-2027
Figure 13: Global Market Shares of Machine Learning in the Life Sciences, by Deployment Mode, 2021
Figure 14: Global Market for Machine Learning in the Life Sciences, by Deployment Mode, 2020-2027
Figure 15: Global Market for Cloud Deployment of Machine Learning in the Life Sciences, 2020-2027
Figure 16: Global Market for On-premise Deployment of Machine Learning in the Life Sciences, 2020-2027
Figure 17: Global Market Shares of Machine Learning in the Life Sciences, by Application, 2021
Figure 18: Global Market for Machine Learning in the Life Sciences, by Application, 2020-2027
Figure 19: Global Market for Machine Learning in Diagnostic Applications, 2020-2027
Figure 20: Global Market for Machine Learning in Therapeutic Applications, 2020-2027
Figure 21: Global Market for Machine Learning in Healthcare Management Applications, 2020-2027
Figure 22: Global Market Shares of Machine Learning in the Life Sciences, by Region, 2021
Figure 23: North American Market Shares of Machine Learning in the Life Sciences, by Offering, 2021
Figure 24: North American Market Shares of Machine Learning in the Life Sciences, by Deployment Mode, 2021
Figure 25: North American Market Shares of Machine Learning in the Life Sciences, by Application, 2021
Figure 26: North American Market Shares of Machine Learning in the Life Sciences, by Country, 2021
Figure 27: U.S. Market for Machine Learning in the Life Sciences, 2020-2027
Figure 28: Canadian Market for Machine Learning in the Life Sciences, 2020-2027
Figure 29: European Market Shares of Machine Learning in the Life Sciences, by Offering, 2021
Figure 30: European Market Shares of Machine Learning in the Life Sciences, by Deployment Mode, 2021
Figure 31: European Market Shares of Machine Learning in the Life Sciences, by Application, 2021
Figure 32: European Market Shares of Machine Learning in the Life Sciences, by Country, 2021
Figure 33: German Market for Machine Learning in the Life Sciences, 2020-2027
Figure 34: U.K. Market for Machine Learning in the Life Sciences, 2020-2027
Figure 35: French Market for Machine Learning in the Life Sciences, 2020-2027
Figure 36: Italian Market for Machine Learning in the Life Sciences, 2020-2027
Figure 37: Spanish Market for Machine Learning in the Life Sciences, 2020-2027
Figure 38: Rest of the European Market for Machine Learning in the Life Sciences, 2020-2027
Figure 39: Asia-Pacific Market Shares of Machine Learning in the Life Sciences, by Offering, 2021
Figure 40: Asia-Pacific Market Shares of Machine Learning in the Life Sciences, by Deployment Mode, 2021
Figure 41: Asia-Pacific Market Shares of Machine Learning in the Life Sciences, by Application, 2021
Figure 42: Asia-Pacific Market Shares of Machine Learning in the Life Sciences, by Country, 2021
Figure 43: New Cancer Cases in China, by Cancer Type/Site, 2020
Figure 44: Distribution of New Cancer Cases in China, by Cancer Type/Site, 2020
Figure 45: Chinese Market for Machine Learning in the Life Sciences, 2020-2027
Figure 46: Japanese Market for Machine Learning in the Life Sciences, 2020-2027
Figure 47: Indian Market for Machine Learning in the Life Sciences, 2020-2027
Figure 48: Rest of Asia-Pacific Market for Machine Learning in the Life Sciences, 2020-2027
Figure 49: New Cancer Cases in Africa, by Cancer Type/Site, 2020
Figure 50: Rest of the World Market Shares of Machine Learning in the Life Sciences, by Offering, 2021
Figure 51: Rest of the World Market Shares of Machine Learning in the Life Sciences, by Deployment Mode, 2021
Figure 52: Rest of the World Market Shares of Machine Learning in the Life Sciences, by Application, 2021
Figure 53: Shares of Machine Learning in the Global Artificial Intelligence Market, 2020
Figure 54: Alteryx: Revenue Snapshot, 2018-2020
Figure 55: Alteryx: Revenue Share, by Business Segment, 2020
Figure 56: Alteryx: Revenue Share, by Region, 2020
Figure 57: Canon Medical: Revenue Share, by Region, 2020
Figure 58: HPE: Revenue Snapshot, 2018-2020
Figure 59: HPE: Revenue Share, by Business Segment, 2020
Figure 60: HPE: Revenue Share, by Region, 2020
Figure 61: IBM Corp.: Revenue Snapshot, 2018-2020
Figure 62: IBM Corp.: Revenue Share, by Business Segment, 2020
Figure 63: IBM Corp.: Revenue Share, by Region, 2020
Figure 64: Intel Corp.: Revenue Snapshot, 2018-2020
Figure 65: Intel Corp.: Revenue Share, by Business Segment, 2020
Figure 66: Intel Corp.: Revenue Share, by Region, 2020
Figure 67: Microsoft Corp.: Revenue Snapshot, 2018-2020
Figure 68: Microsoft Corp.: Revenue Share, by Business Segment, 2020
Figure 69: Microsoft Corp.: Revenue Share, by Region, 2020
Figure 70: Oracle Corp.: Revenue Snapshot, 2018-2020
Figure 71: Oracle Corp.: Revenue Share, by Business Segment, 2020
Figure 72: Oracle Corp.: Revenue Share, by Region, 2020
Figure 73: Phillips Healthcare: Revenue Share, by Region, 2020

Executive Summary

Artificial intelligence (AI) is a term used to identify a scientific field that covers the creation of machines (e.g., robots) as well as computer hardware and software aimed at reproducing wholly or in part the intelligent behavior of human beings. AI is considered a branch of cognitive computing, a term that refers to systems able to learn, reason and interact with humans. Cognitive computing is a combination of computer science and cognitive science.

ML algorithms are designed to perform tasks such data browsing, extracting information that is relevant to the scope of the task, discovering rules that govern the data, making decisions and predictions, and accomplishing specific instructions. As an example, ML is used in image recognition to identify the content of an image after the machine has been instructed to learn the differences among many different categories of images.

There are several types of ML algorithms, the most common of which are nearest neighbor, naïve Bayes, decision trees, a priori algorithms, linear regression, case-based reasoning, hidden Markov models, support vector machines (SVMs), clustering, and artificial neural networks. Artificial neural networks (ANN) have achieved great popularity in recent years for high-level computing. They are modeled to act similarly to the human brain. The most basic type of ANN is the feedforward network, which is formed by an input layer, a hidden layer and an output layer, with data moving in one direction from the input layer to the output layer, while being transformed in the hidden layer.

Companies Mentioned

  • Alteryx Inc.
  • Anaconda, Inc.
  • Canon Medical Systems Corp.
  • Enlitic Inc.
  • Hewlett Packard Enterprise (Hpe)
  • Ibm Corp.
  • Imagen Technologies
  • Intel Corp.
  • Knime AG
  • Microsoft Corp.
  • Nvidia
  • Oracle Corp.
  • Philips Healthcare
  • Sas Institute Inc.

Table Information

Report AttributeDetails
No. of Pages136
PublishedSeptember 2022
Forecast Period2022 - 2027
Estimated Market Value ( USD ) in 2022 $ 3.2 Billion
Forecasted Market Value ( USD ) by 2027 $ 20.7 Billion
Compound Annual Growth Rate45.5%
Regions CoveredGlobal
No. of Companies Mentioned14

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