Related Experiment Video
Updated: Aug 10, 2025

Artificial Intelligence Approaches to Assessing Primary Cilia
Published on: May 1, 2021
Clinical Artificial Intelligence: Design Principles and Fallacies
Matthew B A McDermott1, Bret Nestor2, Peter Szolovits1
1CSAIL, MIT, 32 Vassar St, Cambridge, MA 02139, USA.
None:
Clinical artificial intelligence (AI)/machine learning (ML) is anticipated to offer new abilities in clinical decision support, diagnostic reasoning, precision medicine, clinical operational support, and clinical research, but careful concern is needed to ensure these technologies work effectively in the clinic. Here, we detail the clinical ML/AI design process, identifying several key questions and detailing several common forms of issues that arise with ML tools, as motivated by real-world examples, such that clinicians and researchers can better anticipate and correct for such issues in their own use of ML/AI techniques.
Related Concept Videos
Introduction to Cognitive Psychology
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
Natural and Artificial Concepts
Non-equilibrium in the Cell
Stereotype Content Model
False Memories
One primary source of false memories is misattribution, where individuals incorrectly associate external information...
Reason and Intuition

