Here’s how healthcare CIOs can make AI work for their businesses, CIO News, AND CIO

By Salvi Mittal

There are significant opportunities for AI to improve the healthcare environment. This can range from optimizing workflows to create better efficiencies to improving diagnostics and even early detection of patient care patterns.

For example, AI is invaluable in supporting some of the mundane work of healthcare professionals. For example, AI-based speech recognition systems allow doctors and researchers to dictate notes and fill out forms verbally, freeing up keyboard time for patient care, which deserves more attention anyway. ‘Warning.

Likewise, AI-based computer vision, unlike the human eye, can scan and process thousands of images to detect patterns in dramatically shorter periods of time. This technology can be a huge advantage in medical diagnostics, as it becomes a burden for an overworked radiologist to grasp every nuance of a scan after viewing hundreds of them. In scenarios like these, the AI ​​can help human experts by quickly scanning and prioritizing the images most likely to indicate a problem.

New technologies drive changes in business processes, but organizations need to be agile and open to new opportunities. Considering the large and diverse population of India, it is evident that the country has a lot of potential healthcare data. However, effective training is the key to achieving the desired benefits of AI and to running the right AI models,” said Mike Sicilia, Executive Vice President, Oracle said in an exclusive chat with at the recent Oracle CloudWorld.

“Oracle’s job is to combine this data with the tools and expertise needed to enable our global customers to continue to use AI to improve care delivery. For example, Oracle Cloud Infrastructure provides a comprehensive and secure framework to support the development of new AI models. And our applications integrate AI to help customers realize immediate value in terms of increased automation, efficiency and intelligence,” added Sicilia.

Healthcare prepares to take advantage of AI

Although the pace of industry evolution has not historically matched the speed of technological development, healthcare organizations have begun to make smart, early investments to prepare for the technology-driven future. ‘IA.

“To take full advantage of AI-enabled healthcare delivery, institutions need to modernize data capture and management. They need to move away from generating unstructured data and improve analytics environments, train their workforce to adopt AI-assisted processes to improve efficiency, safety and results in patient care and patient experience,” said Sicilia.

He also talked about the best practices healthcare CIOs need to adopt to deploy successful AI initiatives.

“In the early days of AI, we often found that it was applied without a clear alignment to an intended outcome, leading to many failures. The ability to ingest, standardize, analyze, and return data from “in a way that is immediately actionable by the required stakeholders is critical to the success of these efforts. CIOs need to clearly understand and communicate the goals of the entire organization and align AI efforts accordingly,” said Sicilia. .

“By understanding the results they are trying to achieve, CIOs can create data management strategies that ensure data availability, standardization, quality control, and validity with respect to the data used to form AI models,” he pointed out.

Oracle is partnering with customers across the industry to explore and develop new approaches to modernizing data collection, management, and analysis in cloud environments to embrace AI technologies.

CIOs also need to understand some of the new challenges that AI brings – for example, models can become “stale” over time. Business leaders should also note that bias can seep into AI algorithms based on historical attitudes and data sets and should put safeguards in place to correct for this issue. For example, there has been a historical bias in how different segments of the population are diagnosed and/or treated for medical conditions. Software and people – Data scientists and clinicians from diverse backgrounds are essential to detecting and resolving these issues.

“In short, CIOs should continually review model outputs with their experts and periodically assess whether models need to be updated or retrained with more contemporary data,” he concluded.

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