The Frequency Of Generalised Seizures In Patients Presenting With Acute Ischemic Stroke

Abstract

Artificial Intelligence (AI) can be used in many ways
to improve medical education and curriculum develop
ment. This can involve tailoring the content and delivery of
educational materials to the individual needs of each stu
dent, as well as formative and summative assessments. It
can be used to create scenarios as part of the skills and
simulation experiences and create virtual patients for
learning, hence avoiding the exposure of real patients to
medical students. This editorial will emphasize the basic
concepts of AI and give examples of AI integration in both
undergraduate and postgraduate medical curricula.
Artificial intelligence (AI) fundamentally refers
to the ability of machines to perform tasks that typical
ly require human intelligence. This encompasses many
capabilities, including learning, reasoning, problem-solv
ing, perception (like vision and speech recognition), and
language understanding. 1 Key components of AI include
Machine Learning (ML), Deep Learning (DL), and Natu
ral Language Processing (NLP). It’s important to note that
these components are often intertwined. ML uses artificial
neural networks with multiple layers (hence “deep”) to an
alyze complex data like images, audio, and text. These
networks mimic the structure and function of the human
brain, allowing for extracting high-level features and
representations from raw data. DL focuses on enabling
computers to understand, interpret, and generate human
language. NLP involves tasks such as text analysis, senti
ment analysis, machine translation, and chatbot develop
ment. 2, 3 The most common AI platforms include Gemini
and ChatGPT