Related Experiment Video
Updated: Jan 10, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
From Design to Closure: Artificial Intelligence Transforming Clinical Research
Kanika Vats1, Mohammad Mazhar Alam2
1Department of Research and Innovation, Emirates Classification Society (TASNEEF), Abu Dhabi, ARE.
Artificial intelligence (AI) and machine learning (ML) can significantly improve clinical trials by optimizing patient recruitment, trial design, and data analysis. Responsible adoption, addressing challenges like bias and privacy, is key to enhancing trial efficiency and patient outcomes.
Area of Science:
- Clinical research methodology
- Artificial intelligence in medicine
- Biomedical data science
Background:
- Traditional clinical trials face significant challenges including slow timelines and high costs.
- Artificial intelligence (AI) and machine learning (ML) have emerged as transformative technologies across the clinical research lifecycle.
- AI/ML integration offers potential to revolutionize study design, execution, and analysis.
Related Concept Videos
Clinical Trials
There are four phases in a clinical trial. A phase one...
Clinical Trials: Overview
Issues And Trends In Healthcare Delivery System
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Current Trends in Nursing II
Preclinical Development: Overview

