Review of AI-Enhanced Non-Invasive Biochemical Monitoring in Perioperative Care

A review document summarizing evidence and technologies for non-invasive monitoring of critical biochemical analytes in perioperative care. The document, authored by Xiang Li and last updated in April 2026, focuses on signal processing and clinical applications of AI-enhanced tools. It highlights key analytes like serum potassium, serum calcium, lactate, and blood glucose.

Use Cases

• Surveying current technologies for non-invasive blood gas monitoring based on the review's summary.
• Identifying research gaps for clinical validation of non-invasive analyte monitoring based on the described evidence.
• Exploring integration strategies for AI with traditional monitoring systems based on the review's discussion.
• Investigating signal processing techniques for ECG and PPG waveforms in predicting biochemical changes.

Strengths

• Document is licensed under CC-BY-4.0, allowing for broad reuse.
• File size is 15.2 KB, indicating a concise and focused review.

Limitations

• The dataset is a single 15.2 KB document, which is a very limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare, author Xiang Li

Collection Method

Likely a literature review and synthesis of existing evidence.

Time Range

Review content likely covers research up to its 2026 publication date.

Freshness

Last updated 2026-04-16 04:20:28; freshness should be verified.

Geography

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