Artificial Intelligence In Healthcare Diagnosis Market Increasing Investmentin AI Healthcare Startups Drives Market Growth

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.

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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. The market players are focused on partnerships and collaborations to sustain their position in the market. For instance, in June 2020, Zebra Medical Vision, Inc., collaborated with Apollo Hospitals chain for the deployment of AI-based tools across India, supported by the ?India-Israel Industrial R&D and Technological Innovation Fund.? Moreover, the AI COVID-19 solution will in anticipated collaboration on additional medical findings, such as tuberculosis (TB).

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.

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; Team Fund, USA; and Dream Incubator, Japan, and also saw participation from Invent us 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.

In terms of diagnostic tools, the medical imaging tool segment held the largest share of the artificial intelligence in healthcare diagnosis market in 2019; it is expected to continue to be a leader shareholder during the forecast period. The growth is mainly ascribed to the increasing FDA approvals of AI-based medical imaging tools.However, the automated detection system segment is expected to register the highest CAGR during the forecast period due to increasing adoptionof these tools in infectious disease diagnostics.

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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, Colon Flag (in Europe), or LGI Flag (in the US, and found that the machine-learning algorithm identified.

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