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市場調查報告書
商品編碼
1498608
醫療保健領域的人工智慧市場規模、佔有率、成長分析,按組件、按技術、按應用、按最終用戶、按地區 - 行業預測,2024-2031 年Artificial Intelligence in Healthcare Market Size, Share, Growth Analysis, By Component, By Technology(Machine Learning ), By Application, By End-User, By Region - Industry Forecast 2024-2031 |
2022年人工智慧醫療保健市場規模將為140.9億美元,預測期間(2024-2031年)複合年成長率為38.2%,從2023年的194.8億美元增至2031年的2591.1億美元,預計還會成長。
推動人工智慧在醫療保健領域發展的主要好處包括顯著減少錯誤以及為醫務人員提供強力的支援。人工智慧技術的進步為醫療保健組織提供了 24/7 持續提供病患服務的機會。人工智慧是一個多功能平台,可用於所有部門,實現醫療診斷、影像分析、治療計劃以及 X 光和掃描等程序等功能。它還簡化了業務流程,從回答聊天支援會話中的問題到分析人口健康資料,從而更有效地利用人力並提高為患者提供的專業護理的品質。這種能力使得許多新興企業專注於預測建模,利用人工智慧分析大型資料集並預測未來的醫療保健趨勢。在日常業務中需要管理多個資料輸入的醫療保健組織預計將受益於資料整合和自然語言處理的進一步進步。在歐洲,人工智慧已經被用於支援患者照護和臨床決策,無論是在患者還是在管理方面。例如,生成式人工智慧透過監管業務的自動化,讓護理師可以將直接照護患者的時間增加 20%,從而提高護理人員效率。機器學習技術在醫療保健的各個領域提供了巨大的潛力,包括醫學影像分析、預測分析、個人化治療計劃和藥物分析,有可能徹底改變傳統的醫療實踐。此外,由於對新技術產品的需求不斷增加、現有參與者的擴張以及新參與者的出現,市場預計將成長。
Artificial Intelligence in Healthcare Market size was valued at USD 14.09 billion in 2022 and is poised to grow from USD 19.48 billion in 2023 to USD 259.11 billion by 2031, growing at a CAGR of 38.2% during the forecast period (2024-2031)
The primary benefits driving the growth of AI in healthcare include the significant reduction of errors and robust support for medical staff. Advances in AI technology provide medical organizations with opportunities to offer patient services continuously, 24/7. AI is a versatile platform used across all departments for functions such as medical diagnostics, image analysis, treatment planning, and procedures like X-rays and scans. It also simplifies business processes, from responding to questions in chat support sessions to analysing population health data, thereby enabling more efficient use of manpower and enhancing the quality of professional care provided to patients. This capability has led many startups to focus on predictive modelling, utilizing AI to analyse large datasets and predict future medical developments. Healthcare organizations, faced with the need to manage multiple data inputs in their daily operations, are expected to benefit from further advancements in data integration and natural language processing. In Europe, AI is already being used to support patient care and clinical decision-making in both in-patient and administrative settings. For example, generative AI has improved the efficiency of nurses by allowing them to spend 20% more time directly caring for patients through the automation of regulatory tasks. Machine learning techniques offer significant potential in various fields within healthcare, including medical imaging analysis, predictive analysis, personalized treatment planning, and drug analysis, where they can revolutionize traditional medical practices. Additionally, the market is anticipated to grow due to the increasing demand for new technological products and the expansion of current players, as well as the emergence of new ones.
Top-down and bottom-up approaches were used to estimate and validate the size of the Artificial Intelligence in Healthcare Market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Artificial Intelligence in Healthcare Market Segmental Analysis
The global market for artificial intelligence in healthcare is categorized based on several factors. Components include Hardware (such as processors like MPUs/CPUs, GPUs, FPGAs, ASICs, memory, and network components like adapters, switches, and interconnects), Software (including AI platforms with APIs and machine learning frameworks, and AI solutions available both on-premises and via cloud services), and Services (covering deployment & integration and support & maintenance). Technologies encompass Machine Learning (including deep learning, supervised learning, unsupervised learning, reinforcement learning, and others), Natural Language Processing (IVR, OCR, pattern and image recognition, auto coding, classification and categorization, text analytics, speech analytics), Context-aware Computing (device context, user context, physical context), and Computer Vision. Applications span various areas such as patient data & risk analysis, medical imaging & diagnostics, precision medicine, drug discovery, lifestyle management & remote patient monitoring, virtual assistants, wearables, in-patient care & hospital management, research, emergency room & surgery, mental health, healthcare assistance robots, cybersecurity, and others. End users include hospitals & healthcare providers, healthcare payers, pharmaceutical & biotechnology companies, patients, and others. The market is geographically segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Drivers of the Artificial Intelligence in Healthcare Market
The rise of AI/ML technology in healthcare is driven by the increasing shortage of healthcare professionals. Machine learning models are now being developed to analyze patterns in patient health data, aiding in diagnosis and guiding treatment decisions. Factors such as the Covid-19 pandemic, ongoing mergers and acquisitions, technological partnerships, and government support have significantly accelerated the integration and expansion of AI in healthcare. Initially intended to streamline disease diagnosis, AI/ML algorithms are now widely utilized for identifying Covid-19 positive patients by leveraging comprehensive and personalized patient data.
Restraints in the Artificial Intelligence in Healthcare Market
While AI presents substantial opportunities in healthcare delivery, a critical issue persists: the scarcity of high-quality, curated healthcare data. This limitation poses a significant threat to AI accuracy and consequently patient safety. Challenges in AI implementation include data fragmentation, privacy concerns, and high data acquisition costs, exacerbating the situation. For instance, in November 2023, the WHO issued guidelines addressing the regulatory specifics of AI applications in healthcare. These guidelines emphasize the necessity of robust legal frameworks for data privacy and security to enhance the reliability of AI applications, stressing the importance of collaboration and effectiveness.
Market Trends of the Artificial Intelligence in Healthcare Market
The increasing prevalence of chronic diseases, alongside significant product launches by industry leaders, is a key driver in the healthcare sector's adoption of AI. Our research indicates approximately 9-10 million global cancer deaths in 2023, with an estimated 1,958,310 new cancer cases reported that year. There is a clear emphasis on cancer, tracking various types for new case occurrences. Current statistics on cancer and other persistent illnesses underscore the critical need for precise diagnostic methods and effective treatments. Consequently, the market for AI-driven preventive strategies and early-stage disease detection in healthcare continues to expand rapidly.