US AI in Healthcare market is segmented into AI integrated Hardware, Software and Services.
- AI integrated Hardware includes Processor, Memory and Network.
- Software includes on-premises and cloud solutions along with an AI platform which houses the machine learning framework and the Application Program Interface.
- Services include Deployment and Integration of AI hardware and software solutions, Support and Maintenance.
Based on the technology used, the US AI in Healthcare market is segmented into Machine Learning, Natural Language Processing, Context Aware Computing and Computer Vision.
- Machine Learning has further types like Deep Learning, Supervised Learning, Reinforcement Learning, Unsupervised Learning and others. Imaging and diagnostics, and drug discovery are among the applications that use deep learning. It is also used to automate data analysis to deal with large volumes of data.
- Natural Language Processing is widely used by clinical and research community in healthcare to develop and manage semi-structured and unstructured textual documents, such as electronics health reports, pathology reports, and clinical notes. The demand has risen with increase in number of healthcare institutions structuring and interpreting their data more accurately.
- Context Aware Computing has seen a boom after the development of sophisticated hard and soft sensors.
- Computer Vision has been responsible for significant contributions to the fields of surgery and therapy. This offers precise diagnoses, minimising false positives. Computer vision algorithms are trained to utilise huge amounts of data to detect the presence of a condition which the human doctors might miss owing to their sensory limitations.
By End-Use Application:
Based on the end use application, the market is segmented into patient data and risk analysis, Inpatient care and hospital management, medical imaging and diagnostics, Lifestyle management and remote patient monitoring, Virtual Assistants, Drug discovery, Research, Healthcare Assistance Robots, Precision medicine, Emergency room and surgery, Wearables, Mental Health and Cybersecurity.
- Patient risk algorithms consider several variables and express the results as the percentage risk of developing a major fatal or nonfatal disease in the coming years. They offer solutions that can provide predictive insights into patient health using machine learning and natural language processing algorithms.
- AI and machine-learning methods have the potential to improve the quality and lower the cost of patient care through Clinical Decision Support Systems.
- Healthcare AI start-ups work in the field of Imaging and Diagnostics generating a large volume of challenging data which is simplified with extraction of insights using machine learning. Major start-ups in this field are CureMetrix (California, US), PathAI (Massachusetts, US), Subtle Medical (California, US), Zebra Medical Vision (Israel), Arterys (California, US), Imagen Technologies (New York, US), Viz.AI (California, US), RADLogics (Massachusetts, US), Bay Labs (California, US), Mindshare Medical (Washington, US), Enlitic (California, US), and Proscia (Pennsylvania, US).
- Some of the best AI in Health Start-ups in the US are Roam Analytics, Sopris Health, Artelus, Appto Health, Sense.ly and Atomwise.
- Roam Analytics builds an AI platform for the healthcare industry that uses Natural Language Processing (NLP) to enhance the structure and content of patients’ electronic medical records as well as other AI tools for data analysis and storage.
- Sopris Health offers an AI-powered solution that automates the process of collecting, categorizing, analysing and documenting patients’ symptoms, clinical history and feedback.
- Artelus develops an AI-powered solution that can detect diabetic retinopathy (DR) with high accuracy in under three minutes.
- Appto Health and its AI platform facilitate front-office automation for clinics and healthcare providers, automating patient scheduling, gathering patient feedback and answering organizational questions and more via their phone and messaging AI-powered bots.
- ly and their AI-based virtual nurse Molly helps with prolonged patient monitoring, gathering feedback and symptoms from an individual by using NLP algorithms.
- Atomwise employs the above-mentioned approach to analyse existing medications data and study their contents in order to come up with ways of modifying them to create new types of drugs that would be able to cure a given disease.
By End User:
Based on the end user, the US AI in Healthcare market is segmented into the following:
- Hospitals and healthcare providers, where AI is used to predict and prevent readmissions and improve operations of hospitals
- Patients, where smartphone applications and wearables are targeted to promote the adoption of AI.
- Pharmaceuticals and Biotechnological companies, where drug discovery, precision medicine and research are targeted to drive the use of AI.
- Healthcare Payers, where AI is promoted for use in managing risks, identifying claims, trends and for maximising payment accuracy.
- Others that include patient data, risk analysis etc.
Top 5 Major Players
IBM Corporation, NVIDIA Corporation, Nuance Communications, Microsoft and Intel Corporation are the major players in the Global AI market.
At AMIA 2020, IBM showcased its work related to AI in Healthcare through injection of clinical knowledge and by incorporating an adaptive healthcare system. One such example is Watson for Drug Discovery from IBM Watson Health is a platform that mines text and data in medical literature to identify, assess, and rigorously formalize the relationships among genes, diseases, and drugs to help researchers uncover potential new therapies and find new uses for existing medicines.
NVIDIA develops GPUs and delivers value to its consumers through PC, mobile, and cloud architecture. NVIDIA’s partnership with GSK’s AI powered lab for the discovery of new medicines and vaccines is done on the basis of its expertise in GPU optimization and high-performance computational pipeline development along with its significant contributions to the field through NVIDIA Clara Discovery, NVIDIA DGX A100 systems and so on.
Nuance Communications and Microsoft are focused on transforming patient care with AI powered solutions for physicians, radiologists and hospitals. Microsoft is a global leader offering intelligent tools and solutions that empower clinical and operational efficiency and save costs. Azure Synapse Analytics, Azure Health GitHub Repo, Microsoft Healthcare bot, Azure API for FHIR, Azure AI and ML and Azure IoT for Healthcare are scalable platforms that bring conversational AI to healthcare. Yammer (US), StorSimple (US) and Xamarin (US) are among the subsidiaries of Microsoft in the United States.
Intel Corporation has contributed its significant share to the field of AI by transforming frontline medical care and improving patient experience for a few of their clients. Intel’s technology innovations are enabling the healthcare sector with data-driven insights and artificial intelligence by introducing various tools and solutions to simplify AI deployment in healthcare.
Healthcare Policies and Regulatory Landscape
Recent times have witnessed numerous advancements in the field of healthcare dedicating their successes to Artificial Intelligence. In the last ten years, there has been requirements and guidance for software manufacturers to demonstrate compliance to medical device regulations and to place their products on the market.
In the US, The FDA published a paper for a proposed regulatory framework for modifications to AI or Machine Learning based applications based on current FDA premarket programs, De Novo and Premarket Approval pathways.