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Related Concept Videos

Language01:16

Language

921
Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
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Fischer Projections02:18

Fischer Projections

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Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
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What is Natural Selection?01:32

What is Natural Selection?

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Natural selection is an evolutionary process in which individuals with survival-promoting traits reproduce at higher rates. These favorable traits become more common within a population or species. Naturally selected traits initially arise via random genetic mutations. In order for selection to occur, there must be variation within a population, the trait controlling the variation must be heritable, and there must be an evolutionary advantage for variation in the trait.
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Components of Language01:24

Components of Language

831
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
831
Language Development01:22

Language Development

939
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
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Language and Cognition01:27

Language and Cognition

813
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Related Experiment Video

Updated: Feb 13, 2026

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
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Behind the scenes: A medical natural language processing project.

Joy T Wu1, Franck Dernoncourt2, Sebastian Gehrmann3

  • 1Harvard T.H. Chan School of Public Health, Cambridge, MA, USA; Medical Sieve Radiology, IBM Almaden Research Center, San Jose, CA, USA.

International Journal of Medical Informatics
|March 4, 2018
PubMed
Summary

Multidisciplinary teams are crucial for developing clinically relevant Artificial Intelligence (AI) in healthcare. Collaboration enhances AI research, algorithm development, and addresses data limitations for machine learning applications.

Keywords:
Artificial intelligence in medicineCross-disciplinary researchMachine learningMultidisciplinary teamworkNatural language processingText analyticsTranslational research

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Area of Science:

  • Medical Artificial Intelligence (AI)
  • Healthcare Technology
  • Machine Learning in Medicine

Background:

  • AI in healthcare offers solutions but faces challenges with clinical relevance, unmet expectations, and unclear limitations.
  • Developing effective AI requires addressing the scarcity of labeled datasets for machine learning models.

Purpose of the Study:

  • To share experiences and lessons learned from a two-year multidisciplinary collaboration on a medical Natural Language Processing (NLP) project.
  • To highlight challenges in cross-disciplinary teamwork, dataset creation, and managing expectations for medical AI.

Main Methods:

  • Cross-disciplinary teamwork involving engineers, clinicians, and machine learning experts.
  • Development of AI algorithms and creation of labeled datasets for NLP research.
  • Analysis of challenges encountered during a two-year collaborative research project.

Main Results:

  • Successful collaboration between diverse experts in AI and medicine.
  • Identification of key challenges in medical AI research, including data acquisition and interdisciplinary communication.
  • Insights into setting realistic expectations for current AI capabilities in healthcare.

Conclusions:

  • Multidisciplinary teams are essential for advancing clinically relevant medical AI.
  • Addressing data limitations and fostering effective collaboration are key to successful AI implementation in healthcare.
  • Clear communication and realistic expectation setting are vital for medical AI research and development.