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Related Experiment Video

Updated: Feb 20, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Anesthesia Information Management Systems.

Allan F Simpao¹, Mohamed A Rehman²

¹From the Department of Anesthesiology and Critical Care, Division of General Anesthesia, Perelman School of Medicine at the University of Pennsylvania and The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.

Anesthesia and Analgesia

|October 20, 2017

Summary

This summary is machine-generated.

Anesthesia Information Management Systems (AIMS) have advanced significantly, offering clinical and research benefits. Future applications of AIMS data include machine learning for enhanced perioperative care.

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Area of Science:

Perioperative Medicine
Health Informatics

Background:

Anesthesia Information Management Systems (AIMS) have evolved from basic intraoperative recorders to comprehensive electronic health record (EHR) integrated solutions.
AIMS now manage and document the entire patient perioperative experience.

Observation:

AIMS implementation yields substantial billing, research, and clinical advantages.
Challenges and areas for improvement in AIMS utilization persist.

Findings:

This article reviews the historical development, components, features, benefits, and challenges of AIMS.
The proliferation of AIMS and data sharing enable new analytical approaches.

Implications:

Advanced analytics, including machine learning and visual analytics, can be applied to AIMS data.
These techniques offer potential for further optimization of perioperative care and research.
Continued development and integration of AIMS are crucial for advancing healthcare.