Healthcare Data Collection And Labeling market COVID-19 Impact, Trends & Business Statistics By 2030

Posted by Mrudula Karmarkar on July 12th, 2022

The global healthcare data collection and labeling market size is expected to reach USD 4.5 billion by 2030, based on a new report by Grand View Research, Inc. It is expected to expand at a CAGR of 26.9% from 2022 to 2030. The market is driven by the increased adoption of artificial intelligence and machine learning across the globe. The demand for data labeling is rising due to technological advancements in the industry. Many hospitals and private medical institutions are outsourcing data labeling services for better disease management.

Medical institutions are increasingly using medical data such as videos, images, and patient reports for early and accurate diagnosis of diseases. Medical image labeling provides better diagnosis, prevention, and treatment of diseases than the traditional method of diagnosis. It delivers corresponding results with higher accuracy in the early detection of diseases. It would prove to be one of the powerful methods for future applications in healthcare.

Imaging techniques were extensively used for the diagnosis of COVID-19 during the initial stage. Data collection is crucial for the training of artificial intelligence (AI) algorithms. In association with machine learning, medical imaging diagnostic procedures and AI algorithms have progressed in the recognition of patterns related to disease detection. There was a shortage of medical professionals all over the world at the beginning of the pandemic. Many developed nations opted for AI-assisted solutions to tackle the problem. AI-based data collection and labeling technologies have proved to be useful.

The healthcare industry witnessed the penetration of artificial intelligence and machine learning during the COVID-19 pandemic. The data collection is anticipated to witness growth due to the adoption of technology and medical imaging techniques for the early and accurate diagnosis of diseases. Various market players are undertaking strategic initiatives to build a robust artificial intelligence network by outsourcing data collection and labeling services. For instance, Centaur labs provide medical labeling solutions such as medical audio labeling, medical image labeling, medical text labeling, radiology labeling, ECG labeling, and labeling for cardiology.

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According to the WHO, there were about 247 million confirmed cases of COVID-19 worldwide as of November 2021 with over 5 million deaths. Although RT-PCR testing is still widely used to diagnose COVID-19, there was a shortage of testing kits, and hence reliability of test results was a challenge in many countries. Medical imaging was used in many developed countries to detect the symptoms of COVID-19. Imaging techniques proved to be a powerful tool to minimize the risk of the spread of the virus. In recent years, medical imaging techniques have seen rapid progress due to artificial intelligence, machine learning, and deep learning. Data collection and labeling are used for training these AI algorithms.

Healthcare Data Collection And Labeling Market Report Highlights

  • Based on data type, the image/video segment held the largest revenue share in 2021 as it is majorly used in medical diagnosis and artificial intelligence requires labeled data for training the algorithms
  • The text data type segment is anticipated to expand at a CAGR of 29.1% from 2022 to 2030 as the collection of clinical data, particularly unstructured text documents, has become one of the most significant resources for clinical labeling
  • In 2021, North America dominated the market in terms of revenue owing to the increased adoption of artificial intelligence in the healthcare industry
  • Asia Pacific is likely to expand at the fastest CAGR of 28.4% from 2022 to 2030. This growth is attributed to the increased use of medical imaging in the healthcare industry in China, India, and Japan

List of Key Players of Healthcare Data Collection And Labeling Market

  • Alegion
  • Labelbox, Inc.
  • iMerit
  • Cogito Tech LLC
  • Appen Limited
  • Shaip
  • Snorkel AI
  • Infloks
  • Datalabeller
  • Centaur labs

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Mrudula Karmarkar

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Mrudula Karmarkar
Joined: March 30th, 2020
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