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Global Artificial Intelligence (AI) in Oncology Market to reach USD XX Million by 2028

Global Artificial Intelligence (AI) in Oncology Market Size study, by Treatment (Hemotherapy, Radiotherapy, Immunotherapy, Targeted Therapy, Gene Therapy, And Others) by Type (Lung Cancer, Breast Cancer, Melanoma Cancer, Prostate Cancer, Colorectal Cancer, Among Others), by Application (Diagnosis, Therapy, Prognosis, Health Management, Research) and Regional Forecasts 2022-2028

Product Code: HLSHIT-28771836
Publish Date: 27-09-2022
Page: 200

Global Artificial Intelligence (AI) in Oncology Market is valued at approximately USD XX Million in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2028. Artificial intelligence (AI) is a comprehensive branch of computer science concerned with building smart machines which are capable of performing tasks that typically require human intelligence. The Application of AI tools in Oncology are helpful in finding new approaches for cancer detection, screening, diagnosis and classification, the characterization of cancer genomics, and the analysis of tumor microenvironment. The growing prevalence of Cancer Worldwide and Favorable initiatives from government & non-Government organizations as well as strategic initiatives from leading market players are key factors driving the growth of the Market. Moreover, the government authorities are also supporting the scientists by funding them and giving all the necessary means of support to them. For instance, in 2020, clinicians and scientists from Case Western Reserve University and Cleveland Clinic received an amount of $1.15 Million through National Cancer Institute (NCI) Informatics Technology in Cancer Research (ITCR) program to assist researchers in creating AI-based tools to distinguish tumor recurrence from scar tissue in patients with specific colorectal and brain malignancies who have undergone surgery. Further, the Indian government is planning to initiate more programs to make better healthcare infrastructure by investing around $6.8 Million according to recent reports published by IBEF. Moreover, leading market players are working towards new collaboration to develop an AI platform for Oncology treatment. For instance, Mayo Clinic and Google Health launched a partnership endeavor to investigate the application of AI to radiation therapy in October 2020. Teams from the Mayo Clinic and Google Health would create and verify an algorithm to automatically contour healthy tissue and organs away from tumors using de-identified data. Also, increasing investments in the sector and the growing adoption of AI and related technologies in healthcare would create lucrative growth opportunities for the market during the forecast period. However, a lack of awareness of AI based tools, as well as the dearth of skilled professionals impede market growth throughout the forecast period of 2022-2028.

The key regions considered for the Global Artificial Intelligence (AI) in Oncology Market study includes Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America dominated the space in terms of revenue in 2021, owing to the factors such as the presence of better health facilities, infrastructure, and increasing investment inhealthcare facilities. Whereas, the Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as increasing investments by private players, and the increasing adoption of AI/ML in the sector as well as development in the IT sector specializing in AI-based technologies also accounts to the factor in better growth in this market in the forecasted period.

Major market players included in this report are:
Azra AI
IBM
Siemens Healthineers
Intel
GE Healthcare
NVIDIA
Digital Diagnostics Inc.
Xilinx
InformAI
Enlitic
Day Zero Diagnostics
The objective of the study is to define the market sizes of different segments & countries in recent years and to forecast the values for the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with adetailed analysis of the competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Treatment:
Hemotherapy
Radiotherapy
Immunotherapy
targeted therapy
gene therapy
others
By Type:
lung cancer
breast cancer
melanoma cancer
prostate cancer
colorectal cancer
others
By Application:
Diagnosis
Therapy
Prognosis
health management
research
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, the years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Artificial Intelligence (AI) in Oncology Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Million)
1.2.1. Global Artificial Intelligence (AI) in Oncology Market, by Region, 2020-2028 (USD Million)
1.2.2. Global Artificial Intelligence (AI) in Oncology Market, by Treatment, 2020-2028 (USD Million)
1.2.3. Global Artificial Intelligence (AI) in Oncology Market, by Type, 2020-2028 (USD Million)
1.2.4. Global Artificial Intelligence (AI) in Oncology Market, by Application, 2020-2028 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Artificial Intelligence (AI) in Oncology Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Artificial Intelligence (AI) in Oncology Market Dynamics
3.1. Artificial Intelligence (AI) in Oncology Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Growing prevalence of Cancer Worldwide.
3.1.1.2. Favourable initiatives from government & non-Government organizations.
3.1.1.3. Strategic initiatives from leading market players.
3.1.2. Market Challenges
3.1.2.1. Lack of awareness towards AI-based Technologies
3.1.2.2. Dearth of skilled professional.
3.1.3. Market Opportunities
3.1.3.1. Increasing investments in the sector
3.1.3.2. Growing adoption of AI and related technologies in healthcare.
Chapter 4. Global Artificial Intelligence (AI) in Oncology Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Artificial Intelligence (AI) in Oncology Market, by Treatment
6.1. Market Snapshot
6.2. Global Artificial Intelligence (AI) in Oncology Market by Treatment, Performance – Potential Analysis
6.3. Global Artificial Intelligence (AI) in Oncology Market Estimates & Forecasts by Treatment 2018-2028 (USD Million)
6.4. Artificial Intelligence (AI) in Oncology Market, Sub Segment Analysis
6.4.1. Hemotherapy
6.4.2. Radiotherapy
6.4.3. Immunotherapy
6.4.4. Targeted Therapy
6.4.5. Gene Therapy
6.4.6. Others
Chapter 7. Global Artificial Intelligence (AI) in Oncology Market, by Type
7.1. Market Snapshot
7.2. Global Artificial Intelligence (AI) in Oncology Market by Type, Performance – Potential Analysis
7.3. Global Artificial Intelligence (AI) in Oncology Market Estimates & Forecasts by Type 2018-2028 (USD Million)
7.4. Artificial Intelligence (AI) in Oncology Market, Sub Segment Analysis
7.4.1. Lung Cancer
7.4.2. Breast Cancer
7.4.3. Belanoma Cancer
7.4.4. Prostate Cancer
7.4.5. Colorectal Cancer
7.4.6. Others
Chapter 8. Global Artificial Intelligence (AI) in Oncology Market, by Application
8.1. Market Snapshot
8.2. Global Artificial Intelligence (AI) in Oncology Market by Application, Performance – Potential Analysis
8.3. Global Artificial Intelligence (AI) in Oncology Market Estimates & Forecasts by Application 2018-2028 (USD Million)
8.4. Artificial Intelligence (AI) in Oncology Market, Sub Segment Analysis
8.4.1. Diagnosis
8.4.2. Therapy
8.4.3. Prognosis
8.4.4. Health Management
8.4.5. Research
8.4.6. Others
Chapter 9. Global Artificial Intelligence (AI) in Oncology Market, Regional Analysis
9.1. Artificial Intelligence (AI) in Oncology Market, Regional Market Snapshot
9.2. North America Artificial Intelligence (AI) in Oncology Market
9.2.1. U.S. Artificial Intelligence (AI) in Oncology Market
9.2.1.1. Treatment estimates & forecasts, 2018-2028
9.2.1.2. Type estimates & forecasts, 2018-2028
9.2.1.3. Application estimates & forecasts, 2018-2028
9.2.2. Canada Artificial Intelligence (AI) in Oncology Market
9.3. Europe Artificial Intelligence (AI) in Oncology Market Snapshot
9.3.1. U.K. Artificial Intelligence (AI) in Oncology Market
9.3.2. Germany Artificial Intelligence (AI) in Oncology Market
9.3.3. France Artificial Intelligence (AI) in Oncology Market
9.3.4. Spain Artificial Intelligence (AI) in Oncology Market
9.3.5. Italy Artificial Intelligence (AI) in Oncology Market
9.3.6. Rest of Europe Artificial Intelligence (AI) in Oncology Market
9.4. Asia-Pacific Artificial Intelligence (AI) in Oncology Market Snapshot
9.4.1. China Artificial Intelligence (AI) in Oncology Market
9.4.2. India Artificial Intelligence (AI) in Oncology Market
9.4.3. Japan Artificial Intelligence (AI) in Oncology Market
9.4.4. Australia Artificial Intelligence (AI) in Oncology Market
9.4.5. South Korea Artificial Intelligence (AI) in Oncology Market
9.4.6. Rest of Asia Pacific Artificial Intelligence (AI) in Oncology Market
9.5. Latin America Artificial Intelligence (AI) in Oncology Market Snapshot
9.5.1. Brazil Artificial Intelligence (AI) in Oncology Market
9.5.2. Mexico Artificial Intelligence (AI) in Oncology Market
9.6. Rest of The World Artificial Intelligence (AI) in Oncology Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Azra AI.
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. IBM
10.2.3. Siemens Healthineers
10.2.4. Intel
10.2.5. GE Healthcare
10.2.6. NVIDIA
10.2.7. Digital Diagnostics Inc.
10.2.8. Xilinx
10.2.9. InformAI
10.2.10. Enlitic
10.2.11. Day Zero Diagnostics.
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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