[{"innerBlocks":[],"name":"core\/freeform","postId":644,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"The Department of Veterans Affairs and artificial intelligence vendor DeepMind have developed an AI system that forecasts acute kidney injury in patients.The capability helps clinicians see potential injury early enough so clinicians can intervene to prevent deterioration.The presence of AKI, a deadly kidney disease, is difficult to detect and can have serious consequences\u2014such as the need for dialysis\u2014as the conditions of patients often quickly worsen.However, using the electronic health records of more than 700,000 patients collected from VA sites, researchers developed a deep learning approach that can predict the presence of AKI in patients as much as 48 hours earlier than it can now be diagnosed.

Although the recognition and prompt treatment of acute kidney injury is known to be challenging, our approach may offer opportunities for identifying patients at risk within a time window that enables early treatment,\u201d according to a study<\/a> published Wednesday in the journal Nature<\/i>.Also See<\/b>: Algorithm predicts patients at risk for chronic kidney disease<\/a>Specifically, the AI model accurately predicted more than 90 percent of the most severe AKI cases for patients whose conditions deteriorated so severely that they required dialysis.\u201cIn addition to predicting future acute kidney injury, our model provides confidence assessments and a list of the clinical features that are most salient to each prediction, alongside predicted future trajectories for clinically relevant blood tests,\u201d state the study\u2019s authors.According to DeepMind, this clinical information from the model eliminates the \u201cblack box\u201d problem often associated with AI by helping clinicians understand how the technology makes the predictions and anticipates future patient deterioration.\u201cMoving forward, the VA Palo Alto Health Care System in California will be exploring ways to bring these advances into clinical use,\u201d according to the VA\u2019s announcement. \u201cThe work leading up to this clinical trial involves complex interdisciplinary coordination to build and integrate a user-friendly platform to assist clinicians with treatment decisions.\u201d","saveContent":"The Department of Veterans Affairs and artificial intelligence vendor DeepMind have developed an AI system that forecasts acute kidney injury in patients.The capability helps clinicians see potential injury early enough so clinicians can intervene to prevent deterioration.The presence of AKI, a deadly kidney disease, is difficult to detect and can have serious consequences\u2014such as the need for dialysis\u2014as the conditions of patients often quickly worsen.However, using the electronic health records of more than 700,000 patients collected from VA sites, researchers developed a deep learning approach that can predict the presence of AKI in patients as much as 48 hours earlier than it can now be diagnosed.Although the recognition and prompt treatment of acute kidney injury is known to be challenging, our approach may offer opportunities for identifying patients at risk within a time window that enables early treatment,\u201d according to a study<\/a> published Wednesday in the journal Nature<\/i>.Also See<\/b>: Algorithm predicts patients at risk for chronic kidney disease<\/a>Specifically, the AI model accurately predicted more than 90 percent of the most severe AKI cases for patients whose conditions deteriorated so severely that they required dialysis.\u201cIn addition to predicting future acute kidney injury, our model provides confidence assessments and a list of the clinical features that are most salient to each prediction, alongside predicted future trajectories for clinically relevant blood tests,\u201d state the study\u2019s authors.According to DeepMind, this clinical information from the model eliminates the \u201cblack box\u201d problem often associated with AI by helping clinicians understand how the technology makes the predictions and anticipates future patient deterioration.\u201cMoving forward, the VA Palo Alto Health Care System in California will be exploring ways to bring these advances into clinical use,\u201d according to the VA\u2019s announcement. \u201cThe work leading up to this clinical trial involves complex interdisciplinary coordination to build and integrate a user-friendly platform to assist clinicians with treatment decisions.\u201d","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

AI predicts deadly kidney disease up to 48 hours in advance

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