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Updated: Dec 23, 2025

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
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The evidence landscape in precision medicine.
Spencer Phillips Hey1,2, Cory V Gerlach3,4,5, Garrett Dunlap3,6
1Harvard Center for Bioethics, Harvard Medical School, Boston, MA, USA. spencer_hey@hms.harvard.edu.
Science Translational Medicine
|April 24, 2020
Summary
Precision medicine shows promise, but faces challenges like complex treatments and evidence needs. Evidence landscapes offer a solution to overcome these hurdles in personalized healthcare.
Area of Science:
- Medical research
- Genomics and personalized medicine
Background:
- Precision medicine aims to tailor treatments to individual patients.
- Current challenges include intervention complexity, marker validation, and evidence requirements.
Purpose of the Study:
- To introduce evidence landscapes as a tool to address precision medicine challenges.
- To outline how evidence landscapes can facilitate the integration of precision medicine.
Main Methods:
- This perspective discusses the conceptual framework of evidence landscapes.
- It synthesizes existing knowledge on evidence generation and assessment.
Main Results:
- Evidence landscapes provide a structured approach to evaluating the evidence supporting precision medicine interventions.
- They help clarify the necessary evidence levels for clinical adoption.
Conclusions:
- Evidence landscapes can streamline the validation and implementation of precision medicine.
- This approach aids in overcoming key barriers to effective personalized healthcare.
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