Medical exports by country prediction.

Clinical Decision Support (CDS) provides clinicians, staff, and patients with patient information, usually at the point of care. Clinical Decision Support takes over many routine tasks from clinicians and flags potential problems and solutions for the medical team and patient.

Competitor analysis is the process of understanding your competition in order to succeed in the marketplace. With a proper competitor analysis model, you can benchmark your progress against more established competitors, identify your target market, and even anticipate new products or services from your competition.

Drug discovery covers the whole field of the drug development process, from identifying chemical compounds that could become useful drugs to the clinical trial phase. The drug discovery process is long and complicated, with every stage ripe for implementation of artificial intelligence models.

Machine learning models, referred to as EHRs (electronic health records) or EMRs (electronic medical records), help clinicians better manage patient health records through population management, diagnostics and smart documentation. Clinicians also use these models to perform other clinical tasks.

Banks, credit unions, credit card companies, insurance companies, stock brokerages, investment funds, and more must report their activities to government regulatory agencies. Following financial crises in the late 2000s, regulatory compliance has become stricter and more onerous on financial services companies like those listed above. From the stricter need for reporting and the massive amounts of data generated by financial institutions, the regtech industry has sprung up, combining regulatory reporting and big data technology.

Smart factory technology allows factory sensors to communicate with each other, with employee mobile devices, and with management's software platform. This enables employees to monitor equipment 24/7 and receive immediate alerts whenever there is a problem. The technology also enables the equipment itself to automatically adjust operations in order to keep the factory running smoothly.

AI has been used to improve supply chain and demand forecasting for a couple of decades. Demand planning applications use data driven algorithms to take historical data and use it to forecast. Demand forecasting can include promotion planning or stock and sales forecasting. The machine looks at the forecast, compares it to actual shipments, and suggests alternatives and optimization options. Over time, many companies started doing more specific forecasting for specific regions, products or stores or for more granular points in time. Both retailers and their suppliers (CPG companies or 3rd party shipping and supply chain companies) use their data to help conduct automated decision making within the supply chain.

Trend forecasting is the act of identifying market trends before they come into existence so you can you monitor your market and take advantage of opportunities to meet business goals.