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Intelligence

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The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...

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Related Experiment Video

Updated: Jan 28, 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

Introduction to artificial intelligence in medicine.

Yoav Mintz¹, Ronit Brodie¹

¹a Department of General Surgery , Hadassah Hebrew-University Medical Center , Jerusalem , Israel.

Minimally Invasive Therapy & Allied Technologies : MITAT : Official Journal of the Society for Minimally Invasive Therapy

|February 28, 2019

Summary

Artificial Intelligence (AI) is transforming medicine by enhancing diagnostic accuracy and treatment efficiency. This technology analyzes medical data to augment physician capabilities, paving the way for improved patient care.

Keywords:

artificial intelligence machine learning neural networks

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Area of Science:

Medical Informatics
Computer Science
Artificial Intelligence

Background:

The concept of Artificial Intelligence (AI) dates back to Alan Turing's Turing test and was formally coined by John McCarthy in 1956.
Rapid advancements in computational power enable real-time data evaluation and complex calculations.
AI is now integrated into daily life, including personal assistants, transportation, and gaming.

Purpose of the Study:

To describe the current applications of Artificial Intelligence (AI) in medicine.
To outline the utilization of AI across various medical disciplines.
To discuss future trends and potential of AI in healthcare.

Main Methods:

Machine learning algorithms are employed to analyze diverse medical data.
Evaluation of radiological images and pathology slides using AI.
Analysis of electronic medical records (EMR) to support clinical decisions.

Main Results:

AI enhances diagnostic processes by improving speed and accuracy.
Machine learning aids in patient diagnosis and treatment planning.
AI augments the capabilities of physicians, improving patient care.

Conclusions:

Artificial Intelligence (AI) is increasingly integrated into medicine, improving efficiency and accuracy.
AI applications in radiology, pathology, and EMR analysis are transforming patient care.
The continued development of AI promises significant advancements in future healthcare.