Artificial Intelligence in Healthcare Diagnosis Market is expected to reach US$ 66,811.97 million by 2027

by Sameer Joshi or 13-Apr-2021
Rising adoption of Artificial Intelligence in Disease Identification and Diagnosis, and Increasing Investments in Artificial Intelligence Healthcare Startups Drive Market Growth 
According tour latest study on “Artificial Intelligence in Healthcare Diagnosis Market Forecast t2027 - COVID-19 Impact and Global Analysis by Diagnostic Tool, Application, Service, End User,” the market was valued at US$ 3,639.02 million in 2019 and is projected treach US$ 66,811.97 million by 2027; it is expected tgrow at a CAGR of 44.0% during 2020–2027. The report highlights the trends prevailing in the global artificial intelligence (AI) in healthcare diagnosis market, and drivers and deterrents pertaining tits growth. 
The market growth is mainly attributed tthe rising adoption of AI in disease identification and diagnosis, and increasing investments in AI healthcare startups. However, the lack of skilled workforce and ambiguity in regulatory guidelines for medical software impede the market growth. Furthermore, the increasing potential in emerging economies offers significant opportunities for the growth of the global artificial intelligence in healthcare diagnosis market during the forecast period. 
The healthcare industry has always been at the forefront in terms of innovation and development. Continuous mutations in virulent microbes make it difficult tstay ahead of the prevalence curve. However, with the help of artificial intelligence and machine learning algorithms, the healthcare sector continues tadvance, creating new treatment options as well as helping people live longer and healthier. The Lancet Digital Health, in one of its studies, compared the performance of deep learning (a form of AI) in the diagnosis of diseases using medical imaging versus that carried out by healthcare professionals, by utilizing a sample of studies conducted during 2012–2019. As per the study results, in the past few years, AI has become more precise in identifying disease diagnosis in these images and has become a available source of diagnostic information. With advancements in AI, the efficiency of deep learning-based diagnosis is likely tincrease in the coming years. Moreover, it can help doctors with diagnoses and notify when patients are becoming weak sthat the medical intervention can occur sooner before the need for hospitalization; this can save costs for both hospitals and patients. Additionally, the precision of machine learning enables the detection of diseases such as cancer quickly, thus saving lives.
General Electric Company; Aidoc; Arterys Inc.; icometrix; IDx Technologies Inc; MaxQ AI Ltd.; Caption Health, Inc; Zebra Medical Vision, Inc.; Siemens Healthineers AG; and Koninklijke Philips N.V.; are among the prominent players in the artificial intelligence in healthcare diagnosis market. These players are focused on product development and innovation tsustain their position in the market. For instance, in May 2020, Aidoc received approval from the US Food and Drug Administration for the use of its algorithms for the "adjunctive" detection of findings associated with COVID-19 diagnosis. This solution is among the supporting technologies for  the traditional COVID-19 diagnostic tests procedures, such as serological tests and nasopharyngeal swabs, and others.
The report segments the global artificial intelligence in healthcare diagnosis market as follows:
By Diagnostic Tool
  • Medical Imaging Tool
  • Automated Detection System
  • Others
By Application
  • Eye Care
  • Oncology
  • Radiology
  • Cardiovascular
  • Others
By Service
  • Tele-Consultation
  • Tele Monitoring
  • Others
By End User
  • Hospitals and Clinics
  • Diagnostic Laboratory
  • Home Care
  • Doctors
  • Patients
By Geography
  • North America 
    • US
    • Canada
    • Mexico
  • Europe
    • France
    • Germany
    • Italy
    • UK
    • Russia
  • Asia Pacific (APAC)
    • China
    • India
    • South Korea
    • Japan
    • Australia
  • Middle East and Africa (MEA)
    • South Africa
    • Saudi Arabia
    • UAE
  • South and Central America (SCAM)
    • Brazil
    • Argentina
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