Published Date : 27 Apr 2023
The global artificial intelligence (AI) in oncology industry size will gain around USD 10,680.29 million by 2032 from a valued at USD 891.44 million in 2022, it is growing at a remarkable CAGR of 28.18% from 2023 to 2032.
Oncology uses artificial intelligence (AI) to diagnose cancer more quickly and accurately, which improves patient outcomes and is expected to fuel industry development throughout the projection period.
The field of oncology is being physically altered by artificial intelligence (AI), creating new, significant possibilities for enhancing patient care. Here, we analyze the AI-based products that the Federal Drug Administration (FDA) has already formally approved and demonstrate that cancer detection is the oncology-related field where AI has already made the biggest inroads into clinical practice. Additionally, breast, lung, and prostate cancers are the particular cancer kinds that are now benefiting more from AI-based technology. The potential applications of AI in oncology are discussed. At this point, the biggest obstacles to the 'AI revolution' in oncology are the development of multidisciplinary platforms, understanding the significance of all neoplasms, including rare tumors, and maintaining support for its growth.
Due to factors like the existence of digital infrastructure and advantageous governmental and reimbursement laws, North America is anticipated to control the industry. For instance, according to a September 2022 piece in Elsevier, AI speeds up MRI scans, saving time and money while improving patient results. To democratize healthcare access in the nation and enhance general health results, the government of the United States implements direct payment policies. Thus, one of the major reasons fueling the expansion of the industry under study in North America is a rise in government payments in the United States.
Due to factors like the increased efforts made by governments throughout the region to implement AI services to improve patient health results, Asia Pacific is predicted to grow at a lucrative CAGR of 30.7% during the forecast timeframe. Technologies based on artificial intelligence are being applied in a wide range of commercial, business, and governmental applications. Natural language processing and machine learning are just a couple of the technologies that the phrase is presently used to describe.
Artificial Intelligence (AI) in Oncology Industry Report Scope:
|Market Size in 2022||USD 891.44 Million|
|Projected Forecast Value in 2032||USD 10,680.29 Million|
|Growth Rate||28.18% from 2023 to 2032|
|Largest Market||North America|
|Forecast Period||2023 to 2032|
|Regions Covered||North America, Europe, Asia-Pacific, Latin America and Middle East & Africa|
Additionally, people with lung cancer have a greater chance of contracting the COVID-19 virus. According to a November 2020 piece in the Asian Pacific Journal of Cancer Care, people with cancer, especially those with lung cancer, have weakened immune systems that make them more vulnerable to COVID-19 and other side effects. Additionally, cancer patient detection, therapy, and care during the pandemic were especially difficult due to lockdown limitations. In such situations, modern AI and ML give the potential to enhance cancer patient detection, treatment, and therapy.
Drivers: Multi-omics methods encouraging the AI expectations
The ability to combine various and composite data generated from multi-omics methods to oncologic patients is one of the most encouraging AI expectations. The promising AI tools may be the only ones capable of managing the large quantity of data resulting from various kinds of analysis, including data from DNA sequencing and RNA sequencing. Along these lines, a new surge of AI development has been sparked, with novel possibilities in precision cancer, by the recent publication of American College of Medical genetics standards and recommendations for the analysis of the sequence variants.
Although artificial intelligence (AI) is already being used in oncology clinical practice, more should be done to enable AI to reach its full potential. Our opinion is that the most significant challenges currently facing the completion of the "AI revolution" in oncology are the development of multidisciplinary/integrative developmental views, the immediate recognition of the significance of all neoplasms, including rare tumors, and the ongoing support for ensuring its growth.
Restraints: Healthcare AI uses are not widely known
The administration of enormous datasets and databases, as well as the training and expertise of AI systems and machine learning, pose the biggest challenges to deep learning methods. However, because AI has the potential to reveal sensitive personal information like genetic codes, its use could lead to data breaches.
Lack of openness, the potential for bias in AI algorithms, the use of training data, as well as difficulties with AI incorporation in clinical contexts, are just a few of the problems preventing development.
This article provides a thorough overview of current AI uses in oncology-related fields, with a focus on the AI-based devices that have already received formal clearance to be used in clinical settings. Since its inception, AI has proven to be important across all science disciplines and has the potential to expand significantly in the coming years. This research emphasizes how this increase has drawn attention from oncology and associated fields.
In general, the use of FDA-approved devices has not been designed as a replacement for traditional analysis/diagnostic workflow, but rather as an integrative tool, to be used in certain instances, and possibly as the key improvement to cancer patient care. Currently, the diagnostic fields, which account for the overwhelming majority of authorized devices (>80%), and particularly radiography and pathology, are the sectors of this industry where AI is having a greater effect.
The segment's expansion can be attributed to the increasing number of industry participants who provide software to manage and analyze data and focus on cancer patients who need follow-up care and treatment. Due to the rise of creative companies and entrepreneurialism that offer cutting-edge cancer therapy and prediction solutions, the service sector is also anticipated to expand at the fastest CAGR during the projected timeframe.
Treatment Type Insights:
The chemotherapy-based medicine makes use of drug compounds that kill quickly proliferating cancer cells. A customized digital profile of each patient can be created with the help of AI when it comes to chemotherapy treatment, allowing doctors to adjust the patient's dosage accordingly. The expansion of study efforts for using AI in chemotherapy has sped up sector development.
The expansion of the industry can be attributed to the rising number of FDA clearances as well as comprehensive clinical research showing the effectiveness of immunotherapy. Additionally, the addition of AI contributes to improving the therapy's precision.
One of the main reasons propelling the industry development is the increasing use of AI solutions in clinics to handle the shortage of healthcare workers as well as a quicker cancer diagnosis. For instance, the first organization to use InnerEye, a deep learning application created by Microsoft Research Cambridge, was Addenbrooke's Hospital in Cambridge, United Kingdom. Between 2023 and 2032, diagnostic facilities are expected to grow at the fastest CAGR, thanks to government financing and expanding healthcare programs. Additionally contributing to the development is the evaluation of skilled personnel, cutting-edge machinery, and medicinal specialists.
Major Key Players:
By Cancer Type
By Treatment Type
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