Artificial Intelligence in Medicine

AI Ethics are the set of guiding principles that stakeholders (from engineers to government officials) use to ensure artificial intelligence technology is developed and used responsibly. This means taking a safe, secure, humane, and environmentally friendly approach to AI. 

Taken from Coursera

Algorithm is a set of instructions that is designed to accomplish a task.

Taken from NNLM

Artificial intelligence (AI) refers to the creation of computer systems capable of performing tasks that historically only a human could do, such as reasoning, making decisions, or solving problems. 

Taken from Coursera

Computer Vision is a field of artificial intelligence (AI) that uses machine learning and neural networks to teach computers and systems to derive meaningful information from digital images, videos and other visual inputs—and to make recommendations or take actions when they see defects or issues.  

Taken from IBM

Deep Learning is a subset of machine learning that uses multilayered neural networks, called deep neural networks, to simulate the complex decision-making power of the human brain.

Taken from IBM

Generative AI is a type of artificial intelligence technology that broadly describes machine learning systems capable of generating text, images, code or other types of content, often in response to a prompt entered by a user.

Taken from Tech Republic

Large Language Model (LLM) is a type of artificial intelligence (AI) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content.

Taken from Target Tech 

Machine Learning (ML) is a branch of artificial intelligence (AI) and computer science that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy.

Taken from IBM

Natural Language Processing (NLP) is a subfield of computer science and artificial intelligence (AI) that uses machine learning to enable computers to understand and communicate with human language.

Taken from IBM 

Neural Network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions.

Taken from IBM

Reinforcement Learning is a machine learning (ML) technique that trains software to make decisions to achieve the most optimal results. It mimics the trial-and-error learning process that humans use to achieve their goals.

Taken from AWS

Supervised Learning is a subcategory of machine learning and artificial intelligence. It is defined by its use of labeled data sets to train algorithms that to classify data or predict outcomes accurately.

Taken from IBM 

Transfer Learning uses pre-trained models from one machine learning task or dataset to improve performance and generalizability on a related task or dataset.

Taken from IBM

Turing Test refers to a thought experiment developed in 1950 by Alan Turing, a mathematician, computer scientist, and cryptanalyst, as a way to gauge a machine’s ability to generate human-like communication. Originally called “the imitation game,” the Turing test is a useful tool for studying a machine’s interactions with humans and reflecting on the definitions of “thinking” and “intelligence.” 

Taken from Coursera

Unsupervised Learning also known as unsupervised machine learning, uses machine learning (ML) algorithms to analyze and cluster unlabeled data sets. These algorithms discover hidden patterns or data groupings without the need for human intervention.

Taken from IBM