The document discusses the use of generative AI in healthcare. It defines generative AI as technology that can generate diverse content like images, text, and audio. Generative AI uses neural networks to identify patterns in data and generate new content. It has various applications in healthcare like drug discovery, medical imaging, disease diagnosis, and medical research. The document outlines several use cases of generative AI and factors driving its growth in healthcare. It predicts generative AI will continue transforming healthcare by advancing precision medicine, speeding innovation, and improving disease diagnosis and drug discovery. Overall, the document provides an overview of generative AI applications and potential in the healthcare industry.

1. Generative AI in
Healthcare
Market
“Revolutionizing Healthcare: AI that Creates a Better Tomorrow”

2. Generative AI
• Generative Artificial Intelligence (AI) is defined as the technology
which can generate diverse forms of content, such as images, text,
and audio.
• It enables the users to create new content based on the number of
inputs. Inputs and outputs to these models includes text, images,
sounds, animation, 3D models, or other types of data.
• The AI models make use of the neural networks to identify the
patterns and structures within existing data to generate content.
• From ChatGPT to DALL-E, the latest class of generative AI
applications has emerged from foundation models. These use
complex machine learning systems trained on vast quantities of data
on a massive scale.
• With recent advancement in AI models, the companies now build
specialized image- and language-generating models on top of
these foundation models.
• Most of today’s foundation models are large language models
(LLMs) trained on natural language

3. Generative AI
in Healthcare
• In the new era of transformation, generative AI aims to revolutionize the
healthcare industry. The technology use the advanced machine learning
algorithm to make advancement in the industry.
• Artificial intelligence is transforming the healthcare industry in various ways
ranging from advancement in diagnosis and treatment to enhancing
patient experience and reducing in cost.
• Generative AI make use of deep learning models such as large language
model, and generative adversarial networks to produce realistic and creative
output.
• Generative AI possess the potential to discover novel drugs because of its
capacity to replicate human ingenuity and produce practical and creative
outputs.
• It also helps researchers, scientist, and healthcare professionals to make
significant discoveries, enhance patient care, and solve some of the most
challenging problem in healthcare by using the massive amount of data
stored and modeling complicated biological systems.

4. Why Discussion
on this Topic
• Generative AI in healthcare are important to address due to its various
benefits and application. Some of the application in which generative AI
is widely used are medical imaging, disease diagnosis, drug discovery
and development, and medical research.
• Its potential to transform and improve healthcare outcomes is vast,
making it a highly promising technology in the field.
• It has the potential to address various healthcare challenges such as
chronic disease, shortage of staff, and administration burden.
• Meanwhile, the technology also possess its own challenges and risk,
which should be carefully considered and managed.
• Thus, it is important address the application of generative AI system
which benefit the healthcare industry without compromising the integrity
and quality of healthcare system.

5. Use-Cases
1. Drug Discovery and Development:
Drug discovery and development is an expensive and time-consuming process.
With the advancement in technology and availability of advanced generative AI
models such as Generative Adversarial Networks (GANS) and autoregressive
models, it speed up the drug discovery process by creating new molecules and
predicting their potential efficacy. These models are also used to identify
potential side effects of drugs and optimize the dosage of drugs.
For instance, Insilico Medicine, a generative artificial intelligence (AI) -driven
clinical-stage biotechnology company, developed a drug candidate which is
designed by generative AI, and got the approval for human use, in China. In
June 2023, Insilico Medicine, announced that the first AI drug for COVID-19
has entered the phase II clinical trials.
In addition, in June 2023, researcher at Oxford University and IBM developed
an AI model which can create a molecule to block various virus proteins.

6. 2. Medical Imaging: .
Generative AI is now being used for medical imaging to predict the
inner anomalies of human body. The use of various AI models such as
Generative Adversarial Networks (GANs) and Variational
Autoencoder (VAE) has enabled the healthcare professionals to obtain
more accurate and detailed image of human anatomy.
The CT imaging use the generative AI to lower the amount of
radiation required, which possess a significant benefit in patient
health. It is also used to create a 3-D holographic images from MR
and CT scans to improve surgeons' ability to prepare complex
procedures.
Now-a-days, the hospitals and imaging centers are also using the
generative AI for patient care imaging.
According to Health Data Management, it was reported that around
33.3% of U.S hospitals and imaging centers has already implemented
the AI in radiology section.
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7. 3. Disease Diagnosis: .
The generative AI along aims to detect and diagnosis various
diseases to enhance patient outcomes. It analyzes from a large data
sets and identify diseases based on the data provided in the system.
It allows the physician and healthcare professionals to make more
accurate and timely diagnosis and provide treatment plan for the
patient.
In June 2023, the researcher of Beth Israel Deaconess Medical
Center (BIDMC) tested the accuracy of generative AI model named
chatbot’s to make accurate diagnoses in challenging medical cases.
The team found that the generative AI, Chat-GPT 4, mostly detect
the correct diagnosis in nearly 40% of the cases.
Moreover, in August 2021, researcher has also developed an
advanced deep learning model for diagnosis of cancer by
addressing the issue in gene expression.
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8. 4. Medical Research: .
Generative AI in healthcare are also used in to provide research
ideas. For example, users can leverage ChatGPT in healthcare to
generate ideas by asking questions and getting instant ideas or just
by typing a desired topic.
Generative AIs have become widely used in gene research, where
they help researchers find out how gene expression will change in
response to specific changes in genes. This helps reduce the time
taken to research and accelerates the development of gene
therapies. It also enhances the therapy and treatment by predicting
which treatment the patient’s genes will respond the best.
For instance, in March 2023, NVIDIA, a software company,
announced a set of generative AI cloud services to accelerate the
creation of new proteins and therapeutics, as well as research in the
fields of genomics, biology and molecular dynamics.
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9. • Medical information and education
• Personalized Medicine
• Medical Notetaking
• Clinical Decision Support
• Telemedicine and Remote patient Monitoring
• Synthetic Medical Data
• Medical Device Predictive Maintenance
• Healthcare Robotics
• Natural Language Processing and Virtual
Assistants
• Mental Health Application
Apart from these use
cases some of the other
use cases of generative AI
in healthcare are

10. Factor
contributing
There are various factors contribute toward the growth of generative AI in
healthcare industry.
• Advancement in Technology and AI algorithm: The advancement in
algorithm and different AI model have drive the growth of generative AI in
healthcare setting. These advancement in technology enable more complex
and accurate modeling to enhance the of the outcome. For instance, in March
2023, DiagnaMed, a generative AI healthcare company, announced the launch
of Health GenAI. It focus on the development and commercialization of a
suite of generative AI ready-made and customizable applications powered by
GPT-4 to support the healthcare market in enhancing the patient outcomes,
operational workflow and efficiency.
• Data availability: The generative AI require high quality training data in
order to create meaningful outcome. The availability of diverse and large
healthcare datasets, including imaging data, medical records and genomic
information, enables the training and validation of generative AI models.
Generative AI aims to analyze massive research data sets to forecast potential
health outcomes that can help improve or prevent chronic conditions.

11. Factor
contributing (Cont.)
• Increase in R&D activities: The increase in R&D activities in AI for various
clinical application propel the growth of the generative AI in healthcare industry.
For instance, in June 2023, Clarify Health, one of the leading healthcare
analytics and value based payment solution, announced the launch of Clara,
which is a generative Artificial Intelligence. The Clara enables healthcare
delivery organizations to access valuable insights into behavior changes by
decreasing the cost and increasing the quality of care.
• Industry Adoption and Investment: The healthcare industry has recognized
the potential benefits of generative AI and has started to adopt and invest in
these technologies. Pharmaceutical companies, healthcare providers, and
research institutions are increasingly incorporating generative AI into their
workflows to improve diagnosis, drug discovery, and patient care. The Philips’
Future Health Index 2023, reported that around 83% of the healthcare leader are
planning to invest in AI in the next coming three year. It was also reported that
approximately 74% of healthcare leader have invested in AI, in 2021.
• Regulatory consideration: Regulatory frameworks play a crucial role in
shaping the use of generative AI in healthcare. Regulatory bodies are addressing
issues related to privacy, data security, and patient safety to provide guidelines
and oversight for the development and deployment of generative AI solutions.

12. Future Use
Cases
• The future holds immense potential for generative AI in healthcare. It possess
huge potential for the future of healthcare because of its capacity to develop and
generate valuable outcomes, improve need for precision medicine, speedup the
innovation process, accuracy in disease diagnosis and revolutionize the drug
discovery.
• By utilizing the power of generative AI, healthcare industry can enter the new
era of personalized medicine, virtual clinical trials, real time monitoring &
early warning symptoms, healthcare fraud detection and capable of getting a
deeper understanding of human health.
• In addition, generative AI can substantially increase labor productivity across
the economy, but that will require investments to support workers as they shift
work activities or change jobs. According to McKinsey & Company, it was
reported that around generative AI enhance the labor productivity from 0.1% to
0.4% annually through 2040, depending upon the technology advancement.
• The technology was adopted in healthcare setting while carefully considering
ethical standards and social consequences to enhance healthcare outcome quality
and integrity.

13. Why AMR
Our report on Generative AI in healthcare Market, is a global report, from the 2023-2032. We would like to
inform you that, we provide the market size (USD Million) from years 2022 to 2032 and compound annual
growth rate (CAGR) is estimated from the year 2023 to 2032 (forecast years). In addition, the market
trends, analysis, drivers, constraints, portal five forces, impact of recession on market, for global level are
added in chapter 3. The Global Generative AI in healthcare Market provides the information on Component,
Application, and End User segments. The component include Software and Services. On the basis of
application, the market is bifurcated into Synthetic Data & Image Generation, Disease Diagnosis, Drug
Discovery & Development, Medical Research, Clinical Decision Support, and Others. The end user
includes Hospitals & Clinics, Research & Diagnostic Centers, and Others. As per our standard syndicate
report template, we provide company profiles information for ten major companies which will cover
company overview, company snapshot, operating business segments, product portfolio, business
performance (overall company revenue) and key strategy moves & developments (2021-2023).
Please Note: The information about company profile will be provided as per availability of data in public
domains.
“The scope of the report will include the revenue generated from the sale of software of generative AI
in healthcare sector. The revenue will also include the services provided by generative AI in
healthcare.”