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AI in Diagnostics Market to Surpass USD 6341.68 Million by 2031 Owing to Rising Demand for AI-powered Diagnostics Tools

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The global AI in Diagnostics Market is experiencing a surge, driven by several factors including the increasing demand for AI tools in medical imaging, rising government initiatives to support AI adoption, and growing investor funding in AI-powered startups. This trend is expected to propel the market to reach a staggering valuation of USD 6341.68 Million by 2031, reflecting a significant compound annual growth rate (CAGR) of 23.49% throughout the forecast period from 2024 to 2031.

AI in Diagnostics Market
AI in Diagnostics Market

List of AI in Diagnostics Market Companies Profiled in Report:

  • Aidence B.V.
  • Aidoc
  • AliveCor Inc.
  • Digital Diagnostics Inc.
  • GE Healthcare
  • Imagen Technologies
  • Neural Analytics
  • Riverain Technologies
  • Siemens Healthineers
  • Vuno, Inc.
  • Zebra Medical Vision, Inc.

Download Free Sample Report of AI in Diagnostics Market @ https://www.snsinsider.com/sample-request/1849

A Wave of Innovation

The AI in Diagnostics Market is witnessing a significant boost due to various factors. These include the rising demand for AI tools in medical imaging, particularly for assisting radiologists in their workload and improving diagnosis accuracy. Additionally, government initiatives worldwide are actively encouraging the adoption of AI-based technologies in healthcare, further propelling market growth. Furthermore, the influx of funding for AI-powered startups is fostering continued innovation and development in the field.

For instance, incorporating AI into imaging devices has the potential to significantly enhance diagnostic accuracy. A research article published in the Journal of the American Medical Association titled “An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy from a Multicenter Study” (December 2021) reported that an AI algorithm outperformed human radiologists in detecting pulmonary nodules on chest X-rays. This highlights the promising potential of AI in medical imaging.

Moreover, the increasing global funding for AI startups is fueling the integration of AI into various diagnostic imaging modalities. For example, Qure.ai, a health-tech company that leverages AI for medical imaging diagnostics, raised USD 40 million in March 2022. The company plans to utilize these funds to expand its global presence and accelerate the development of products for critical care and community diagnostics. Such fundraising activities are expected to significantly contribute to market growth.

Opportunities Abound: Market Analysis

Advancements in healthcare information technology infrastructure, coupled with continuous advancements in cloud storage, computer processing power, and machine learning algorithms, are paving the way for the seamless integration of AI-powered systems in diagnostics. This allows for efficient and accurate diagnoses, enabling care providers to formulate timely and appropriate treatment plans. Pathology and radiology services are witnessing a widespread adoption of AI-based algorithms. For instance, AI-powered radiology solutions can analyze vast datasets from various imaging modalities, offering radiologists a comprehensive and accurate analysis.

The rising global incidence rate of chronic diseases is directly contributing to the surge in demand for early diagnosis and initial treatment management plans. This trend is positively impacting the development and growth of the AI in Diagnostics Market. For instance, according to the World Health Organization (WHO) estimates from 2018, the global cancer prevalence rate was 18.1 million and is projected to reach 22 million by 2034. Since early detection is crucial for managing most chronic diseases, the adoption rate of AI-based diagnostics is expected to rise steadily. These advanced solutions empower care providers to devise preventive and proactive treatment plans, shifting the focus from reactive approaches.

The demand for AI-based solutions has soared in the diagnostics industry due to their immense potential in medical image diagnosis. These solutions offer faster analysis of diagnostic images, efficient interpretation of minute data points often missed by radiologists, and improved image triage and clinical decision support. Radiologists can leverage these solutions to shift their focus from image interpretation to providing better patient care. A study by the Association of American Medical Colleges suggests that the shortage of radiologists could reach nearly 42,000 by 2033. With a limited number of radiologists,  the pressure to interpret vast quantities of diagnostic data is immense. AI-based solutions offer a welcome respite in this scenario.

Emerging Markets: A Profitable Landscape

Emerging markets such as India, China, and Brazil are anticipated to present significant growth opportunities for players in the AI in Diagnostics Market. This growth can be attributed to the expanding patient population in these countries. India, for instance, is estimated to have 2 to 2.5 million cancer patients at any given time, with approximately 0.7 million new cases reported annually, according to the National Institute of Health and Family Welfare. Furthermore, the healthcare sectors in emerging economies like India and China are witnessing rapid expansion with the introduction of new medical technologies, particularly advanced imaging equipment.

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Key Market Segmentation

By Component

  • Software
  • Hardware
  • Services

By Diagnosis Type

  • Cardiology
  • Oncology
  • Pathology
  • Radiology
  • Chest and Lung
  • Neurology
  • Others

Segment Analysis: X-Rays Segment Stays Dominant

The X-rays segment is poised to dominate the AI in Diagnostics Market throughout the forecast period.  Since X-rays are the most commonly performed imaging tests in radiology departments, AI has the potential to significantly improve triage, interpretation, and overall workflow efficiency. Integrating AI into X-ray analysis enhances speed, accuracy, ease of access, and workflow, reducing turnaround times and boosting patient safety.  These advantages are expected to propel the demand for AI in X-rays, propelling segment growth.

Additionally, a recent article titled “These Algorithms Look at X-Rays-and Somehow Detect Your Race” (August 2021) highlighted the significant investments being made by market players to develop AI software for interpreting X-rays and identifying conditions that doctors might miss, such as lung tumors.  Furthermore, as mentioned earlier, these algorithms can detect subtle data points in scans that may be overlooked by human radiologists.  Such advancements and the growing adoption of AI in X-ray analysis are expected to be key drivers for segment growth.

The launch of new products by industry players is another factor anticipated to propel segment growth. For instance, in August 2021, Fujifilm received approval from Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) for CXR-AID, a chest X-ray program powered by AI. CXR-AID, developed using Lunit’s AI technology, can identify significant abnormalities such as chest nodules, consolidation, and pneumothorax from X-ray images.

Key Regional Development: North America Takes the Dominant Position

North America dominates the AI in Diagnostics Market and is expected to maintain its leading position throughout the forecast period. The increasing use of advanced technology in healthcare systems and the rising burden of chronic diseases in the region are driving market growth.

For instance, according to the American Cancer Society’s Cancer Facts and Figures 2022, published in January 2022, an estimated 1.9 million new cancer cases will be diagnosed in the US in 2022. This highlights the high prevalence of cancer and other chronic diseases, which necessitates accurate diagnosis and treatment.  This, in turn, fuels the adoption of AI for early diagnosis, ultimately propelling market growth.

Key Takeaways: Unveiling the Value of the Report

  • Gain a comprehensive understanding of the current market size and projected growth trajectory for the global AI in Diagnostics Market through 2031.
  • Identify the key factors propelling market expansion, alongside potential roadblocks that may hinder growth.
  • Explore the dominance of the X-ray segment and delve into the performance of other notable segments within the market.
  • Uncover the reigning position of North America and the promising prospects emerging in key regions like India, China, and Brazil.
  • Stay ahead of the curve with insights into strategic initiatives undertaken by prominent players in the market.

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Table of Content

Chapter 1 Introduction

Chapter 2 Research Methodology

Chapter 3 AI in Diagnostics Market Dynamics

Chapter 4 Impact Analysis (COVID-19, Ukraine- Russia war, Ongoing Recession on Major Economies)

Chapter 5 Value Chain Analysis

Chapter 6 Porter’s 5 forces model

Chapter 7 PEST Analysis

Chapter 8 AI in Diagnostics Market Segmentation, By Component

Chapter 9 AI in Diagnostics Market Segmentation, By Diagnosis Typer

Chapter 10 Regional Analysis

Chapter 11 Company profile

Chapter 12 Competitive Landscape

Chapter 13 Use Case and Best Practices

Chapter 14 Conclusion

Continued…

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