Artificial Intelligence In Healthcare Diagnosis Market: Increasing Investment in AI Healthcare Startups Drives Market Growth

The artificial intelligence in healthcare diagnosis market was valued at US$ 3,639.02 million in 2019 and is projected to reach US$ 66,811.97 million by 2027; it is expected to grow at a CAGR of 44.0% during 2020–2027.

Artificial intelligence (AI) uses algorithms and software to perform certain tasks without human intervention and instructions. AI represents the integration of technologies such as machine learning, natural language processing, reasoning, and perception. It is used in healthcare for approximation of human cognition as well as the analysis of complex medical and diagnostic imaging data. The artificial intelligence in healthcare diagnosis market is driven by the ability of AI to provide improved outcomes; moreover, the growing need to increase coordination between healthcare workforce and patients also supports the market growth. The rise in the importance of Big Data in healthcare, increase in the adoption of precision medicine, and surge in venture capital investments also contribute to the market growth.

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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.

Based on diagnostic tool, the artificial intelligence in healthcare diagnosis market is segmented into medical imaging tool, automated detection system, and others. In 2019, the medical imaging tool segment accounted for the largest share of the market. The growth of the segmental market is attributed to the rising number of FDA approvals for the AI-based medical imaging tools.

Factors such as the rising adoption of artificial intelligence in disease identification and diagnosis and increasing investments in AI healthcare startups are driving the growth of the AI in healthcare diagnosis market. However, the lack of skilled workforce and ambiguity of regulatory guidelines for medical software impede the market growth. Further, the increasing potential in emerging economies offers significant opportunities for the future growth of the global artificial intelligence in healthcare diagnosis market players.

Artificial Intelligence in healthcare is one of the most significant technological advances in medicine thus far. Startups developing AI-driven imaging & diagnostic solutions are the major factors responsible for the growth of the market in the study period. China, the US, and the UK are emerging as a popular hub for healthcare innovations. China-based healthcare AI startups have benefited from the government’s AI-focused development strategy, inspiring investment, and private-public partnerships. Additionally, the British government has announced a National Artificial Intelligence Lab that will collaborate with Britain’s universities and technology companies to research on cancer, dementia, and heart disease. UK-based startups have benefited from the government’s robust library of patient data, as British citizen’s share their anonymous healthcare data with the British National Health Service.

Tokyo-based AI Medical Service, the Japanese startup developing the AI-powered technology to detect cancerous lesions from endoscopic footage, announced in October 2019 that it had secured about USD $43 million US (about 4.6 billion yen) in a Series B round. Healthcare analytics firm Tricog has raised USD $10.5 million in a Series B round of funding. Using Artificial Intelligence and Machine Learning, the startup helps in the wellness, screening, and diagnosis of acute as well as chronic heart diseases. The investment comes in from UTEC - The University of Tokyo Edge Capital, Japan; Aflac Ventures, LLC, Japan; TeamFund, USA; and Dream Incubator, Japan, and also saw participation from Inventus Capital and Blume Ventures. Using Artificial Intelligence and Machine Learning, the five-year-old startup has helped 3 million patients globally. It also uses its virtual cardiology services to help in remote clinics.

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A team of researchers from Beth Israel Deaconess Medical Center of Harvard Medical School, led by Dr. Andrew Beck, showed that data analysis through deep-learning decreased the error rate in breast cancer diagnosis by 85%. Machine learning algorithms were also been tested for the examination of melanoma by the researchers of Stanford University. Apart from reviewing the diagnostic skills of the tool, the researchers results were reviewed by certified dermatologists. Also, artificial intelligence can classify skin cancer as accurately as dermatologists. Further, the researchers studied the commercially available tools for the discovery of colorectal cancer, ColonFlag (in Europe), or LGI Flag (in the US, and found that the machine-learning algorithm identified.

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