Quest Diagnostics enters a generated AI partnership with Google Cloud
Companies across the healthcare industry want to expand their AI capabilities, which often work with large tech players for years.
This week, Quest Diagnostics became one of them. The diagnostic giant announced a new partnership with Google Cloud to deliver new AI capabilities including predictive population health analysis, customized physician outcome reports and personalized patient engagement.
In collaboration, Quest will use Google Cloud's data analytics and generation AI technologies (including Google Agentspace), which uses generative AI to express data and automate tasks.
One of the goals of this collaboration is to generate personalized health insights for patients.
“We are still exploring the potential applications of generating AI, and the impact of this new relationship on patients. A potential use case involves reminding patients that if the data indicates they expire but have not done so, follow-up or annual appointments can be scheduled,” Quest Clare said.
He noted that the collaboration also aims to enable clinicians to prepare access to integrated laboratory data.
Claire notes that laboratory tests and results can provide clinicians with important insights about patient health and help guide treatment plans.
“The completeness of the patient's laboratory data helps doctors provide the best care. Over time, the correlation between trends and different laboratory results helps doctors make up the completeness of patient health.”
Clare said that using a key metric task to measure the success of its partnership with Google Cloud will be the level of complex reports that typical business users can generate through natural language prompts.
This will reduce the time analysts spend creating interim reports, he said, making them more dedicated to “real data science efforts.”
Shweta Maniar, the company's global director of healthcare and life sciences, noted that Google Cloud's generative AI has many applications in the diagnostic world.
“It can process, analyze and reduce silos in the huge and complex data generated in modern healthcare – from genomic information to medical images, more efficiently than humans, which can help providers understand what other diagnostic therapies may be needed. This leads to faster and more accurate diagnosis, enabling early diagnosis and better patient diagnosis,” she explains. ”
AI can also mark subtle patterns and abnormal situations in data that may evade the human eye, making it possible to discover new insights into the disease and predict personal risks, Maniar said.
She also highlighted the role of AI in personalized medicine, saying the technology can help tailor treatment and prevention strategies for each patient based on its unique characteristics and data.
Photo: Galeanu Mihai, Getty Images
