In a dataset of 25 patients who were clinically diagnosed as COVID-19 negative cases, a 2020 NCBI study found that 68% of COVID-19 positive cases were correctly identified by AI-based algorithms. The adoption of AI/ML technologies to enhance patient care, decrease machine downtime, and lower care costs is one of the key factors fueling the expansion of the healthcare industry. Diagnostics, patient management, medication management, claims management, workflow management, machine integration, and cybersecurity have all seen a significant increase in the integration of AI/ML technologies.
According to Data Bridge Market Research, Artificial Intelligence in Healthcare Market is USD 9.64 billion in 2022, is expected to reach USD 272.91 billion by 2030, at a CAGR of 51.87% during the forecast period 2023 to 2030
“Rise in adoption of AI/ML technologies surge market demand"
The adoption of AI/ML technologies was prompted by the growing shortage of healthcare professionals. AI algorithms can be trained to analyze patient health data as a result, helping medical professionals identify a patient's condition and come up with a successful treatment strategy. The ongoing Covid-19 pandemic, increased mergers and acquisitions, technological partnerships, and supportive government initiatives all contributed significantly to market expansion and hastened the adoption of AI in healthcare. Following their initial application in the quick and accurate diagnosis of medical conditions, AI/ML algorithms are now widely used in the detection of Covid-19 positive patients using personalized patient information and data consolidation. These are the specific elements that fuel market expansion.
What restraints the growth of artificial intelligence in the healthcare market?
"Lack of standardization and regulation can impede the market growth”
The lack of standardized guidelines and regulations specific to AI in Healthcare creates challenges for its widespread adoption. The absence of clear regulatory frameworks leads to uncertainty and hesitation among healthcare providers and organizations. The development of standardized guidelines, ethical frameworks, and regulatory policies specific to AI in healthcare is necessary to address concerns regarding safety, accountability, and ethical implications. Clear regulations will provide a framework for the responsible and effective use of AI technologies in healthcare.
Segmentation: Global Artificial Intelligence in Healthcare Market
The artificial intelligence in healthcare market is segmented on the basis of type offering, technology, end-user and application.
- On the basis of offering, the artificial intelligence in healthcare market is segmented into hardware, software, service.
- On the basis of technology, the artificial intelligence in healthcare market is segmented into machine learning, deep learning, querying method, natural language processing, context- aware computing, and computer vision.
- On the basis of application, the artificial intelligence in healthcare market is segmented into robot-assisted surgery, virtual assistants, administrative workflow assistants, connected machines, diagnosis, clinical trials, fraud detection, cyber security, dosage error reduction, real-time monitoring, precision medicine, personal health and nursing assistants, drug development and discovery, diagnostic and clinical decision support, others.
- On the basis of end user, the artificial intelligence in healthcare market is segmented into acos and mcos, patients, payers, pharmaceutical and biotechnology companies, providers healthcare payers, others.
Regional Insights: North America dominates the Global Artificial Intelligence in Healthcare Market
North America dominates the artificial intelligence in the healthcare market because due to the region's robust healthcare infrastructure, growing investment from major players in the development of advanced devices, high adoption of minimally invasive procedures, accessibility to reimbursements, growing geriatric population, high healthcare spending combined with the emergence of the Covid-19 pandemic, and the growing number of research activities.
Asia-Pacific is expected to grow at the highest growth rate in the forecast period of 2023 to 2030 owing to the rising medical tourism, expanding research activities in the area, an increasing geriatric population, and an increase in government initiatives to raise awareness all contribute to the region's growing need for high-quality healthcare.
To know more about the study, visit, https://www.databridgemarketresearch.com/reports/global-artificial-intelligence-in-healthcare-market
Recent Developments in Global Artificial Intelligence in Healthcare Market
- In 2020, To encourage statewide AI adoption for autonomous monitoring, care.ai and the Texas Hospital Association (THA) have announced a partnership.
- In 2020, Aidoc and Imbio worked together to incorporate AI technologies into medical image analysis for the detection and management of pulmonary emboli. In addition, a growing number of startups focused on AI-based healthcare technologies are being recognized by venture capitalists and receiving investments from them.
The prominent key players operating in the Global Artificial Intelligence in Healthcare Market Include:
- NVIDIA Corporation (U.S.)
- Intel Corporation (U.S.)
- IBM (U.S.)
- Google LLC (U.S.)
- Microsoft (U.S.)
- General Vision Inc. (U.S.)
- Johnson & Johnson Services, Inc. (U.S.)
- Siemens Healthcare GmbH (Germany)
- Medtronic (Ireland)
- CloudMedx Inc. (U.S.)
- Agfa-Gevaert Group (Belgium)
- Oncora Medical (U.S.)
- Imagia Cybernetics Inc. (Canada)
- Micron Technology, Inc. (U.S.)
- DeepMind Technologies Limited (U.K.)
- Welcome AI (U.S.)
- Koninklijke Philips N.V. (Netherlands)
- Precision Health AI (U.S.)
- Cloud Pharmaceuticals, Inc. (U.S.)
Above are the key players covered in the report, to know about more and exhaustive list of artificial intelligence in healthcare market companies contact, https://www.databridgemarketresearch.com/contact
Research Methodology: Global Artificial Intelligence in Healthcare Market
Data collection and base year analysis are done using data collection modules with large sample sizes. The market data is analyzed and estimated using market statistical and coherent models. In addition, market share analysis and key trend analysis are the major success factors in the market report. The key research methodology used by dbmr research team is data triangulation which involves data mining, analysis of the impact of data variables on the market, and primary (industry expert) validation. Apart from this, data models include vendor positioning grid, market time line analysis, market overview and guide, company positioning grid, company market share analysis, standards of measurement, global vs regional and vendor share analysis. Please request analyst call in case of further inquiry.
