Generative AI in Healthcare Market Size is Expanding Around USD 21.74 Billion by 2032
Ottawa, July 10, 2023 (GLOBE NEWSWIRE) -- As per Precedence Research, the U.S. generative AI in healthcare market size will reach at USD 8.7 billion by 2032. Generative AI, refers to a class of artificial intelligence algorithms used in various fields, including healthcare. The algorithms in generative AI are capable of creating new data instances, such as images, text, or even sounds, that are similar to the training data it has been exposed to. The discriminator network, on the other hand, tries to distinguish between real and generated data. These two networks work together in a competitive process, with the generator trying to produce increasingly realistic outputs, and the discriminator getting better at identifying the generated samples.
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The healthcare sector is being rapidly transformed by artificial intelligence (AI). Doctors and other healthcare professionals are benefiting greatly from the insights AI is giving them about patient care because of its capacity to analyze massive volumes of data and spot trends. Generative AI is one kind of AI that has a lot of promise for the healthcare industry.
Regional Insights
North America is expected to hold the largest market share during the forecast period. The region has a strong ecosystem of collaboration between industry and academia. Technology companies are partnering with research institutions and healthcare providers to develop and implement generative AI solutions in healthcare. These collaborations facilitate the exchange of knowledge, expertise, and resources, leading to the development of innovative generative AI applications and their successful integration into the healthcare system.
Moreover, the region has a well-defined regulatory landscape that governs the use of generative AI in healthcare. Regulatory bodies such as the U.S. Food and Drug Administration (FDA) provide guidelines and frameworks for the development, validation, and deployment of generative AI technologies in healthcare settings. This regulatory framework ensures patient safety, data privacy, and the effectiveness of generative AI applications.
Europe is expected to hold a significant market share over the forecast period. European countries have made progress in promoting interoperability and data sharing across healthcare systems. Initiatives such as the European Electronic Health Record Exchange Format (EHR-EX) aim to facilitate the exchange of health data between different countries and healthcare providers. Generative AI can leverage interoperable data to develop robust models and insights that span larger patient populations, contributing to more accurate diagnoses and treatment recommendations. Thus, this is expected to drive the market growth in the region.
Report Highlights
By application, the clinical segment is expected to hold the largest share of the market, generative AI models can assist in predicting diseases, estimating disease progression, and personalizing treatment plans based on individual patient characteristics.
the clinical segment is expected to hold the largest share of the market, generative AI models can assist in predicting diseases, estimating disease progression, and personalizing treatment plans based on individual patient characteristics. By function , the workflow & administrative tasks segment is expected to grow at the fastest rate over the forecast period. Generative AI can support decision-making in healthcare administration by providing insights and recommendations. By analyzing various data sources, including financial data, operational metrics, and patient outcomes, generative AI models can generate actionable insights and suggestions for optimizing resource allocation, budgeting, and strategic planning. This supports data-driven decision-making and helps healthcare administrators make informed choices. In addition, this can assist in managing and analyzing electronic health records, which contain vast amounts of patient data. Generative AI models can extract relevant information from unstructured data, such as clinical notes, and convert it into structured formats for easier analysis and retrieval. This improves the efficiency of data management, enables data-driven decision-making, and enhances patient care coordination, driving the growth of the market.
the workflow & administrative tasks segment is expected to grow at the fastest rate over the forecast period. Generative AI can support decision-making in healthcare administration by providing insights and recommendations. By analyzing various data sources, including financial data, operational metrics, and patient outcomes, generative AI models can generate actionable insights and suggestions for optimizing resource allocation, budgeting, and strategic planning. This supports data-driven decision-making and helps healthcare administrators make informed choices. In addition, this can assist in managing and analyzing electronic health records, which contain vast amounts of patient data. Generative AI models can extract relevant information from unstructured data, such as clinical notes, and convert it into structured formats for easier analysis and retrieval. This improves the efficiency of data management, enables data-driven decision-making, and enhances patient care coordination, driving the growth of the market. By end-user, the diagnostic centers segment dominates the market, generative AI models can provide automated preliminary assessments, highlight potential areas of concern, and offer second opinions to enhance diagnostic accuracy and efficiency.
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Scope of this report
Coverage Details Market Size in 2030 USD 11.9 Billion in 2030 CAGR 35.14 from 2023 to 2032 U.S. Market Size USD 8.7 Billion in 2032 North America Market Share 37% in 2022 Asia Pacific Market Share 25% in 2022 Key Players Syntegra, NioyaTech, IBM Watson, Microsoft Corporation, Saxon, Tencent Holdings Ltd., Neuralink Corporation, Google LLC, Johnson & Johnson, OpenAI, Oracle, and Others
Market Dynamics
Drivers
Rising focus on improving patients care
Personalized treatment plans for patients may be developed using generative AI. To create a personalized strategy, the algorithm can look at a patient's medical history, genetic information, lifestyle preferences, and other aspects. The program, for instance, may look at a patient's tumor DNA and identify the genetic abnormalities responsible for the disease. It can then make a precise, tailored therapy recommendation for a selected genetic mutation. Additionally, generative AI can help medical professionals forecast patient outcomes. It can find patterns connected to certain outcomes by learning from vast datasets of patient data and assist in making informed decisions. Thus, improved patient care is expected to propel the growth of the market over the forecast period.
Restraint
Ethical and privacy concerns
The use of generative AI in healthcare raises ethical and privacy concerns. Generating artificial data that closely resembles real patient information requires careful handling of sensitive and private healthcare data. Protecting patient privacy, ensuring informed consent, and implementing robust data anonymization techniques are critical considerations. Striking the right balance between data utility and privacy preservation is essential. Thus, to some extent ethical and privacy concerns are one of the biggest restraints for the market expansion.
Opportunities
Rising drug discovery and development acitivities
Generative AI is revolutionizing the drug discovery and development process. By generating novel molecular structures and compounds, generative AI models can aid in identifying potential drug candidates and accelerating the discovery timeline. Generative AI can also predict drug-target interactions, optimize lead compounds, and assist in repurposing existing drugs for new indications. This can potentially speed up the development of innovative therapies and address unmet medical needs. Thus, this is expected to offer a lucrative opportunity for market growth during the forecast period.
Challenges
Regulatory and compliance challenge
The healthcare industry is heavily regulated to safeguard patient safety, privacy, and data security. Integrating generative AI technologies into healthcare workflows requires compliance with various regulatory frameworks such as data protection regulations (e.g., GDPR in Europe), healthcare privacy laws (e.g., HIPAA in the United States), and medical device regulations. Adhering to these regulations can pose challenges and may necessitate additional validation and approval processes.
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Recent Development
In May 2023, FormGPT.io, a generative AI data collecting and analysis solution for the healthcare sector, has been launched by DiagnaMed Holdings Corp., a provider of generative AI healthcare solutions. As part of its commitment to roll out a portfolio of ready-made and customized generative AI apps powered by GPT-4 to assist real-world circumstances in enhancing patient outcomes, operational workflow, and efficiency, the Company created FormGPT.io (www.FormGPT.io), its first commercial offering. Targeting licensed medical practitioners, hospitals, and life science firms, FormGPT.ai was created using the Company's development expertise and features of its patented generative AI brain health platform, CERVAI.
Market Segmentation
By Application
Clinical Cardiovascular Dermatology Infectious Disease Oncology Others
System Disease Diagnosis Telemedicine Electronic Health Records Drug Interaction
By Function
AI-Assisted Robotic Surgery
Virtual Nursing Assistants
Aid Clinical Judgment/Diagnosis
Workflow & Administrative Tasks
Image Analysis
By End User
Hospitals & Clinics
Clinical Research
Healthcare Organizations
Diagnostic Centers
Others
By Geography
North America
Europe
Asia-Pacific
Latin America
Middle East and Africa
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