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The artificial intelligence in medical diagnostics market was valued at USD 1.22 billion in 2023. It is expected to grow at a CAGR of 36.1% during the forecast period of 2024-2032 and attain a market value of USD 19.55 billion in 2032.
The market value is impacted by the increasing use of these platforms and ongoing technological advancements in this field. There has been a significant increase in patent applications associated with artificial intelligence in medical diagnostics, driven by the ability of diagnostic tools improved by the ongoing advancements in AI algorithms, deep learning technologies, and machine learning models, which result in faster and more accurate diagnosis.
The Global Artificial Intelligence in Medical Diagnostics Patent Landscape Report provides a comprehensive and in-depth analysis of the patents in this growing industry. The key sections captured in the report for global Artificial Intelligence in Medical Diagnostics includes a thorough examination of the patent portfolios of key players, covering aspects such as the number of patents and types of technologies patented. It includes the latest trends, geographical distribution of patents, top IP player profiles, technological segmentation, and patent valuation. The breakdown of patents by technical segments is provided, giving more clarity on the specific areas of innovation within artificial intelligence in medical diagnostics technologies.
Machine Learning (ML) algorithms are trained on massive datasets to find trends and forecast future events. Machine learning models are increasingly used in medical diagnostics to help diagnose diseases by analyzing imaging data, patient records, and lab results. Therefore, such technical innovations are expected to have a significant impact on the patent landscape.
Artificial intelligence in medical diagnostics refers to the process of analyzing medical data to diagnose illnesses and conditions using cutting-edge AI technologies like machine learning and deep learning. It can majorly help in interpreting medical images, reviewing patient records, and forecasting disease outcomes. Artificial intelligence (AI) systems also increase diagnostic accuracy, efficiency, and speed. These innovations enable personalized medicine and help medical professionals make better decisions.
Artificial intelligence in the medical diagnostics market continues to evolve, driven by the lack of radiologists and other diagnostic specialists in the world. This makes artificial intelligence an alluring replacement to help with clinical decision-making. Also, the adoption of advanced diagnostic technologies is being aided by investments in healthcare infrastructure, especially in developing regions is a driving factor to boost market value in the forecast period.
Technological Advancements in Artificial Intelligence is Expected to Boost the Market Growth
The efficiency and accuracy of diagnosis is greatly improved by advances in AI technologies. The medical diagnostics market adopts diagnostic tools more widely because of these advancements that increase their effectiveness, improving patient outcomes and fueling market growth.
For instance, in July 2021, the AlphaFold Protein Structure Database was released as a collaborative project between EMBL-EBI and AlphaFold. Approximately 365,000 proteins, or nearly the entire UniProt proteome of humans and 20 model organisms were predicted through the AlphaFold protein structure models after its launch. The introduction of such new tools and enhanced products in the market influences the patent landscape as researchers and companies take effective measures to secure patents and protect their innovations.
Growing Demand for Personalized Medicine is Expected to Propel the Artificial Intelligence in Medical Diagnostics Industry Growth
AI is being used in medical diagnostics due to the growing demand for customized treatment regimens. The transition to more efficient, individualized healthcare solutions is supported by its capacity to evaluate massive datasets and offer customized diagnostic insights. Increased application of artificial intelligence is expected to boost the number of patent applications in the coming years.
The report provides an in-depth analysis of the patents in this field by the following segmentation -
Breakup by Type
Breakup by Application
The breakup based on type includes software and services. Artificial intelligence in medical diagnostics investigations has been conducted with the chosen patent families labelled based on the types to which they pertain. Big data analytics in medical diagnostics, processing and analysing large amounts of data is essential. To support diagnostic decisions, big data analytics allows the integration and analysis of various data sources, such as patient histories, genomic data, and real-time monitoring data.
The detailed technological data will be provided for all specified segments classified in this report.
The United States is one of the leading jurisdictions for artificial intelligence in medical diagnostics patents, having around 24,500 patents. The presence of a well-established healthcare infrastructure, a robust legal framework and prominent research institutions engaged in innovations contributes to the patent landscape significantly.
In the Asia-Pacific, China is another vital jurisdiction and is witnessing rapid growth in patent filings. The expanding healthcare landscape in the region contributes to the evolving research capabilities, thereby influencing a surge in patent applications.
Among the players with artificial intelligence in medical diagnostics patent families, new entrants have been identified, which can be either established companies or startups developing their first technology in the field. Some of the major companies mentioned in this report (a non-exhaustive list) are as follows:
IBM Corp.
IBM Corp. improves medical diagnostics with cutting-edge AI technologies through its Watson Health division. The business's AI-powered systems examine enormous datasets, such as genetic and medical records, to produce accurate diagnosis insights and tailored treatment recommendations that enhance patient outcomes.
Nvidia Corp
A well-known tech business with a focus on AI computing and GPU production. Nvidia's AI platforms and potent GPUs make it easier to develop and implement cutting-edge AI models in medical diagnostics. This allows for the quicker and more accurate analysis of medical images and data, improving diagnostic capabilities and healthcare solutions.
Other companies include LG Corp., Koninklijke Philips Nv, Qualcomm Inc., Siemens Healthcare Gmbh, Qualcomm Inc., Strong Force Iot Portfolio 2016 LLC, Cilag Gmbh Int, Ethicon LLC, Gen Electric, Kpn Innovations LLC, Ge Prec Healthcare LLC, Tran Bao, Yue Henry, Baughn Mariah R, Genaissance Pharmaceuticals, Paige Ai INC, Tang Y Tom, Medtronic INC, Rom Tech INC, Tempus Labs INC, Ubiome INC, Univ Johns Hopkins, Yao Monique G, Incyte Genomics INC, Univ California, Flextronics Ap LLC, Lu Dyung Aina M, Elliott Vicki S, Gandhi Ameena R, Hello INC, Strong Force Tx Portfolio 2018 LLC, Lal Preeti G, Hafalia April J A, Verint Americas INC, Chawla Narinder K, Gecko Robotics INC, Ramkumar Jayalaxmi, Dexcom INC, Intuitive Surgical Operations, Intel Corp, Automotive Tech Int, Lu Yan, Nguyen Danniel B, Ericsson Telefon Ab L M among others.
The Global Artificial Intelligence in Medical Diagnostics Patent Report provides information on the intellectual property (IP) position and strategy of key players. This report can help companies and players looking to enter or invest in this field by:
Scope of the Report | Details |
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*While we strive to always give you current and accurate information, the numbers depicted on the website are indicative and may differ from the actual numbers in the main report. At Expert Market Research, we aim to bring you the latest insights and trends in the market. Using our analyses and forecasts, stakeholders can understand the market dynamics, navigate challenges, and capitalize on opportunities to make data-driven strategic decisions.
1 Introduction
2 Executive Summary
3 Global Artificial Intelligence in Medical Diagnostics Market Overview
3.1 Global Artificial Intelligence in Medical Diagnostics Market Historical Value (2017-2023)
3.2 Global Artificial Intelligence in Medical Diagnostics Market Forecast Value (2024-2032)
4 Global Artificial Intelligence in Medical Diagnostics Market Segmentation
4.1 Global Artificial Intelligence in Medical Diagnostics Market Share by Type
4.1.1 Market Overview
4.1.2 Software
4.1.3 Services
4.2 Global Artificial Intelligence in Medical Diagnostics Market Share by Application
4.2.1 Market Overview
4.2.2 Neurology
4.2.3 Radiology
4.2.4 Oncology
4.2.5 Others
4.3 Global Artificial Intelligence in Medical Diagnostics Market Share by End User
4.3.1 Market Overview
4.3.2 Hospitals
4.3.3 Diagnostic Centre
4.3.4 Others
5 Global Market Dynamics
5.1 Market Drivers and Constraints
5.2 Porter’s Five Forces Analysis
5.3 PESTEL Analysis
5.4 Industry Events, Initiatives, and Trends
5.5 Value Chain Analysis
6 Global Artificial Intelligence in Medical Diagnostics Patent Landscape Analysis
6.1 Patent Distribution by Publication Year
6.2 Patent Distribution by Application Year
6.3 Patent Distribution by Priority Year
6.4 Analysis by Type of Patent
6.4.1 Granted Patents
6.4.2 Patent Application
6.4.3 Amended Application
6.4.4 Search Report
6.5 Analysis by Legal Status
6.5.1 Active
6.5.2 Pending
6.5.3 Expired/Discontinued
6.6 Analysis by Patent Jurisdiction
6.7 Analysis by Patent Age
6.8 Analysis by Cooperative Patent Classification (CPC) Codes
6.9 Average Time to Publish a Patent
6.9.1 By Entities
6.9.2 By Jurisdiction
6.9.3 By Technology
6.10 Analysis by Type of Entity (Academic and Non-Academic)
6.11 Analysis by Top Applicants
6.12 Analysis by Top Inventors
7 Global Artificial Intelligence in Medical Diagnostics Patent Analysis by Technology
7.1 Total Patents by Top Technologies
7.2 Time Evolution of Patents by Technology
7.3 Emerging Technologies
7.4 Patent Segmentation, By Type
7.4.1 Time Evolution by Number of Patents
7.4.2 Time Evolution by Number of Patent Families
7.4.3 Analysis by Type of Entity (Academic vs Non-Academic)
7.4.4 Analysis by Top Applicants
7.4.5 Analysis by Top Inventors
7.5 Patent Segmentation, By Application
*Complete technology list will be provided in the report.
8 EMR Patent Valuation Analysis
8.1 Assessment Methodology
8.2 High Value Patents
8.3 Medium Value Patents
8.4 Low Value Patents
9 Global Artificial Intelligence in Medical Diagnostics – Top 10 Players Patent Analysis
9.1 Top 10 Entities by Number of Patents
9.2 Analysis by Publication Year
9.3 Analysis by Application Year
9.4 Analysis by Priority Year
9.5 Analysis by Type of Patent
9.6 Analysis by Jurisdiction
9.7 Analysis by Cooperative Patent Classification (CPC) Codes
9.8 Analysis by Source of Innovation
9.9 Analysis by Forward and Backward Citations
9.10 Analysis by Legal Status
9.11 Analysis by Patent Age
9.12 Analysis by Key Inventors
9.13 Entity Dynamics
9.13.1 Analysis by Type of Player (Academic vs Non-Academic)
9.13.2 Analysis by Collaboration
9.13.3 Analysis by Technology
9.13.4 Newcomers
9.13.4.1 Start-up Companies
9.13.4.2 Established Companies
10 Patent Profile of Key Players
10.1 Samsung Electronics Co Ltd
10.1.1 Product Portfolio
10.1.2 Patent Portfolio by Patent Families
10.1.3 Time Evolution of Patents
10.1.4 Geographical Patent Coverage
10.1.5 Patent Analysis by Technology
10.1.6 Patent News and Developments
10.1.7 Financial Analysis
10.1.8 SWOT Analysis
10.2 Qualcomm Inc .
10.3 LG Corp .
10.4 IBM Corp .
10.5 Nvidia Corp
10.6 Koninklijke Philips NV
11 Future Trends
12 Global Artificial Intelligence in Medical Diagnostics Market Landscape (Additional Insight) *
12.1 Global Artificial Intelligence in Medical Diagnostics: Developers Landscape
12.1.1 Analysis by Year of Establishment
12.1.2 Analysis by Company Size
12.1.3 Analysis by Region
12.2 Global Artificial Intelligence in Medical Diagnostics: Product Landscape
12.2.1 Analysis by Type
12.2.2 Analysis by Application
*Additional insights are not provided in the standard report.
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