The global artificial intelligence in cancer diagnostics market size is expected to reach USD 8,390.1 million by 2032, according to a new study by Polaris Market Research. The report Artificial Intelligence in Cancer Diagnostics Market Share, Size, Trends, Industry Analysis Report, By Application (Screening & Diagnosis, Tumor Identification, Surveillance, Treatment); By Cancer Type; By End-Use; By Region; Segment Forecast, 2023 - 2032” gives a detailed insight into current market dynamics and provides analysis on future market growth.
AI has become a powerful tool for detecting abnormal cell growth and improving early-stage cancer diagnosis. With machine learning, AI algorithms can effectively identify the presence of cancer cells and predict their development. The demand for early and accurate cancer detection has propelled the introduction of AI technologies in cancer diagnostics, contributing to the industry's growth.
Globally, cancer remains a major cause of mortality, claiming approximately 10 million lives in 2020 alone, as reported by the World Health Organization (WHO). By enabling early detection, AI can potentially prevent many of these deaths, emphasizing its importance in the fight against cancer.
The utilization of AI in cancer screening and diagnosis holds immense potential for early detection, driving the market's growth. AI and machine learning models can analyze pathology and radiology images, providing precise cancer diagnoses compared to observations based solely on doctors' experience. A notable example is the development of an AI algorithm in 2019 by researchers from the National Institutes of Health and Global Good.
This algorithm accurately analyzes digital images of women's cervix, identifying potentially cancerous precancerous changes. This breakthrough highlights the transformative impact of AI in enhancing cancer diagnostics and is expected to fuel market growth in the future.
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AI offers a powerful solution for detecting abnormal cell growth in the body, particularly in the early stages of cancer. Through machine learning techniques, AI and ML can effectively identify and monitor the growth of cancer cells. It is crucial to a growing demand for early and accurate cancer detection. The introduction of AI technologies in cancer diagnostics is expected to impact the industry's growth positively.
However, it is important to note that the COVID-19 pandemic harmed the demand for AI in cancer diagnosis. The focus of the healthcare sector shifted towards managing the increasing number of COVID-19 cases, due to a temporary slowdown in the implementation of AI technologies in cancer diagnostics.
Artificial Intelligence in Cancer Diagnostics Market Report Highlights
Polaris Market Research has segmented the artificial intelligence in cancer diagnostics market report based on application, cancer type, end-use, and region:
Artificial Intelligence in Cancer Diagnostics, Application Outlook (Revenue - USD Million, 2019 - 2032)
Artificial Intelligence in Cancer Diagnostics, Cancer Type Outlook (Revenue - USD Million, 2019 - 2032)
Artificial Intelligence in Cancer Diagnostics, End-Use Outlook (Revenue - USD Million, 2019 - 2032)
Artificial Intelligence in Cancer Diagnostics, Regional Outlook (Revenue - USD Million, 2019 - 2032)
Report Attributes |
Details |
Market size value in 2023 |
USD 875.4 million |
Revenue forecast in 2032 |
USD 8,390.1 million |
CAGR |
28.5% from 2023 – 2032 |
Base year |
2022 |
Historical data |
2019 – 2021 |
Forecast period |
2023 – 2032 |
Quantitative units |
Revenue in USD million and CAGR from 2023 to 2032 |
Segments Covered |
By Application, By Cancer Type, By End-Use, By Region |
Regional scope |
North America, Europe, Asia Pacific, Latin America; Middle East & Africa |
Key Companies |
IBM, Sophia GeneticsTempus, Janssen Pharmaceutica, Microsoft, Cerner Corporation, RaySearch Laboratories, Google Deep Mind, Flatiron, Oncora Medical, Whiterabbit.ai, Ibex Medical Analytics, Oncology Analytics, Inc, 4baseCare, Path AI, Oracle, Therapixel, OncoHealth, Pfizer, and Others. |
For Specific Research Requirements |