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Radometech

AI in "Healthcare"

The fragmented nature of the healthcare supply chain costs billions in value and reduces the healthcare sector's ability to overcome the challenge it faces.

Business Challenges

 

Although AI plays a vital role in Healthcare, there are very few discussions about the role AI and Machine Learning in the healthcare supply chain, compared with other areas, such as improved disease diagnosis and drug development. The healthcare industry is facing many changes that pose new challenges to healthcare organizations big and small. In particular, the fast-evolving government regulations, technological innovations, and patient expectations create a new environment in which running a medical practice isn’t just about treating patients anymore.

 

 

 

How can AI help?

Artificial intelligence has the potential to transform the healthcare industry in monumental ways. Improving the healthcare supply chain could give people around the world access to safer and more affordable medications and devices. It can also reduce costs and create additional revenue sources for manufacturers. One of the most underestimated areas is data governance. The beauty of AI is that it can analyze large amounts of data to identify patterns and hidden correlations that would otherwise take humans considerably longer to decipher, if at all.

 

 

 

Use cases

Supply Standardization: Some of the provider-preferred items can be extremely costly, but standardizing them is a challenging task. Physicians lack the time and resources required to compare the associated costs and patient outcomes when assessing options in the marketplace. However, AI could provide doctors with tools that give them real-time statistics about how certain supplies perform. Such information makes a supply standardization goal more straightforward.

 

Inventory Level Optimization: Health systems must speedily and accurately assess the demand for inventory. Otherwise, providers may hoard supplies to avoid running out, or delays could occur while waiting for replenishments. Hospitals often use the time-series method of forecasting demand. It uses past usage trends to predict future needs. AI can improve upon traditional time-series forecasting by allowing health systems to continually update forecasts. AI also gets smarter with use.

 

Operating Room Throughput: Having the right supplies on hand is crucial in an operating room. Any supply-related mishaps could cause patient complications, as well as frustration for the responsible surgeons. AI will revolutionize the operating room and materials manager’s ability to plan for and deliver critical supplies at the right time and place, and at the right cost. 

 

Procedural Throughput: The opportunities to cut costs by applying AI and machine learning to SCM don’t stop at operating room procedures. They extend to any other treatments happening within hospital operations. With the data-driven insights provided, health care facility managers can become more informed about the average supply-related expenses for particular procedures and make adjustments when necessary.

 

 

 

Why choose us?

The application of artificial intelligence in healthcare industry is a win-win for all— improving supply chain efficiencies, lowering operating costs, and leading to improved patient outcomes.

 

We at RadomeTech believe AI is crucial for every business entity. Thus we have a developed a tool which lets the user have the power of Artificial Intelligence and Machine Learning !

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Copyright Radome Techologies and Services Pvt Ltd 2020

Use Cases

Prognostic Health Monitoring

Everyday we operate and work with different machineries and at some point, in time, they breakdown. Though with the advancement of technologies, we can predict the downtime so that we are ready with the alternate, Prognostic Health Management (PHM) systems are some of the main protagonists of the Industry 4.0 revolution.
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Use Cases

Prognostic Health Monitoring

Everyday we operate and work with different machineries and at some point, in time, they breakdown. Though with the advancement of technologies, we can predict the downtime so that we are ready with the alternate, Prognostic Health Management (PHM) systems are some of the main protagonists of the Industry 4.0 revolution.
READ MORE

Load More

Prognostic Health Monitoring

Everyday we operate and work with different machineries and at some point, in time, they breakdown. Though with the advancement of technologies, we can predict the downtime so that we are ready with the alternate, Prognostic Health Management (PHM) systems are some of the main protagonists of the Industry 4.0 revolution.

Asset health monitoring, AI, prognostics, diagnostics, predictive maintenance

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Prognostic Health Monitoring

Everyday we operate and work with different machineries and at some point, in time, they breakdown. Though with the advancement of technologies, we can predict the downtime so that we are ready with the alternate, Prognostic Health Management (PHM) systems are some of the main protagonists of the Industry 4.0 revolution.

Asset health monitoring, AI, prognostics, diagnostics, predictive maintenance

Read more

Load More

Prognostic Health Monitoring

Everyday we operate and work with different machineries and at some point, in time, they breakdown. Though with the advancement of technologies, we can predict the downtime so that we are ready with the alternate, Prognostic Health Management (PHM) systems are some of the main protagonists of the Industry 4.0 revolution.

Asset health monitoring, AI, prognostics, diagnostics, predictive maintenance

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TELECOMMUNICATION

According to sources, 19% of Telecom companies are adopting AI by 2023 and 58% of Service providers see AI crucial for Network Management.

ANALYSE PERFORMANCE DATA
AUTOMATION OF NETWORK MANAGEMENT
SPOT ANOMALIES IN NETWORK TRAFFIC
IMPROVE NETWORK CAPACITY PLANNING

OIL & GAS

Oil  & gas is one of the most lucrative industries, it is also one of the most dangerous. According to experts, 50% of Oil & gas industries say they have already begun AI to help solve challenges at their organisations.

OPTIMIZE PRODUCTION AND MAINTENANCE COST
ENHANCE QUALITY ASSURANCE
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DEFECT DETECTION
ABILITY TO MAKE BETTER DECISIONS

REAL ESTATE

Experts believe that 16% of the Real Estate companies are adopting AI in their businesses by 2023 and are expected to see a marginal profit of around 50%

IMAGE RECOGNITION & ANALYSIS
ANALYSE PATTERNS
RISK FORECASTING
OPTIMIZE SCHEDULES
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What we do.

We craft unisex leather bags and accessories for those, who appreciate premium handmade products, durable quality and urbane style.

AI for Healthcare

In the complex world of Healthcare, AI tools can support healthcare providers to provide faster service, diagonse issues and analyse data to identify trends or genetic information that would predispose someone to a particular disease.

AI ASSISTED MEDICAL DIAGNOSIS
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MEDICAL RISK PREDECTION
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AUTOMATED WORKFLOW ASSISTANCE
MEDICAL IMAGE ANALYSIS
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Use Case

Aircrafts require a vast spectrum of parts to operate ranging from high cost repairable parts to low cost fast moving consumables Apart from the fact that certain parts are highly expensive, failure to have the necessary part readily available can also translate into expensive AOG (aircraft on ground) incidents.

Manufacturing

Experts believe that about 40% revenue boot will be there upon adopting to AI in Manufacturing. Around 50% of the manufacturers are planning to Invest on AI for their processes.

DETECTS FAULTS
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REDUCE UNPLANNED DOWNTIME
PREDICTIVE MAINTENANCE
Quality control

Retail

According to sources, 85% of customer interaction in retail will be managed by AI by 2023 and a revenue growth of 10% on adopting AI in the business process.

DEMAND FORECASTING
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SUPPLIER PERFORMANCE PREDECTION
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OPTIMIZE INVENTORY
ROUTE OPTIMIZATION