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Related Experiment Video

Updated: Jul 15, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

AI agents in clinical practice: an evidence map.

Joy Xu¹, Justin M Ko², Joseph C Kvedar³

¹David Geffen School of Medicine, Los Angeles, CA, USA. joyxu@mednet.ucla.edu.

NPJ Digital Medicine

|July 13, 2026

Summary

Autonomous AI, or agentic AI, is transforming digital medicine. Responsible adoption requires proactive governance, auditability, and clinician oversight for safe integration into patient care.

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Last Updated: Jul 15, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

Digital medicine
Artificial intelligence in healthcare
Clinical informatics

Background:

Autonomous AI systems (agentic AI) represent a significant advancement in healthcare technology.
Agentic AI is increasingly being explored for applications across the healthcare spectrum.
Current adoption patterns show a concentration in administrative tasks with expansion into clinical workflows.

Purpose of the Study:

To synthesize evidence on the adoption of agentic AI in digital medicine.
To identify opportunities for agentic AI implementation across diagnostics, management, and operations.
To highlight critical considerations for the responsible integration of agentic AI into clinical practice.

Main Methods:

A perspective-based synthesis of current evidence and trends.
Review of early deployments and applications of agentic AI.
Analysis of the clinical patient journey and care-adjacent operations.

Main Results:

Early agentic AI applications are primarily in administrative workflows.
Agentic AI adoption is rapidly expanding into the clinical patient journey.
Key areas for application include diagnostics, patient management, and operational efficiency.

Conclusions:

Agentic AI presents a pivotal inflection point for digital medicine.
Responsible translation into clinical practice necessitates proactive governance.
Auditability and clinician oversight are crucial for safe and effective agentic AI deployment.