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Related Concept Videos

Pain01:20

Pain

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Pain serves as a critical warning signal that alerts the body to potential or actual harm. When mechanical pressure on the skin is intense, such as from a sharp pinch, the sensation transitions from touch to pain. Similarly, extreme temperatures, like a hot pot handle, convert the sensation of heat into pain. Pain can also result from overstimulation of other senses, such as blinding light, loud noise, or the intense heat from habañero peppers. This ability to sense pain is essential for...
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Nociception01:44

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Nociception—the ability to feel pain—is essential for an organism’s survival and overall well-being. Noxious stimuli such as piercing pain from a sharp object, heat from an open flame, or contact with corrosive chemicals are first detected by sensory receptors, called nociceptors, located on nerve endings. Nociceptors express ion channels that convert noxious stimuli into electrical signals. When these signals reach the brain via sensory neurons, they are perceived as pain.
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Empathy02:34

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Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
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Analgesia and Pain Management01:25

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Pain is critical to various clinical pathologies, provoking an urgent need for effective management. Pain, whether acute or chronic, is a complex neurochemical process. Its alleviation depends on the type, with nonopioid analgesics effective for mild to moderate pain, such as musculoskeletal or inflammatory pain, while neuropathic pain responds best to anticonvulsants, tricyclic antidepressants, or serotonin/norepinephrine reuptake inhibitors. For severe acute or chronic pain, opioids may be...
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Spinal Cord: Cross-sectional Anatomy01:16

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The cross-sectional anatomy of the spinal cord offers a detailed view of its complex structure and function within the central nervous system. At the core of the spinal cord lies the gray matter, characterized by its butterfly or "H"-shaped appearance in cross-section. This central region is enveloped by white matter, with the overall structure divided into symmetrical halves by the dorsal median sulcus and the ventral median fissure.
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Spinal Cord: Information Processing01:10

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The spinal cord is an integral hub for motor and sensory information that enables the brain to communicate with the peripheral nervous system (PNS). This communication consists of relaying sensory data and transmission of motor commands.
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Related Experiment Video

Updated: Jul 5, 2025

Author Spotlight: Quantifying Pain Experience – An Illustrative Approach Using the Pain Body Diagram
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Development of a Knowledge Graph Embeddings Model for Pain.

Jaya Chaturvedi1, Tao Wang1, Sumithra Velupillai1

  • 1Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, United Kingdom.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 15, 2024
PubMed
Summary
This summary is machine-generated.

This study models pain concepts using knowledge graph embeddings derived from electronic health records and SNOMED CT. This approach enhances understanding of pain by representing complex relationships for better computational analysis.

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Area of Science:

  • Medical Informatics
  • Computational Linguistics
  • Knowledge Representation

Background:

  • Pain is a complex phenomenon with interconnected concepts, crucial for understanding patient health.
  • Modeling pain from electronic health records (EHRs) is challenging due to data complexity.
  • Knowledge graphs offer a structured way to represent pain-related concepts and relationships.

Purpose of the Study:

  • To construct knowledge graph embedding models for pain concepts.
  • To integrate information from unstructured mental health EHRs with structured medical knowledge (SNOMED CT).
  • To evaluate the effectiveness of these models on a link prediction task.

Main Methods:

  • Extracted pain concepts and relations from unstructured EHR text.
  • Utilized SNOMED CT to incorporate external medical knowledge.
  • Developed and trained knowledge graph embedding models.
  • Evaluated models using a subject-object link prediction task.

Main Results:

  • The constructed knowledge graph embedding models demonstrated effectiveness in representing pain-related concepts and their relationships.
  • Performance was evaluated against baseline models on the link prediction task.
  • The models successfully integrated heterogeneous data sources (EHRs and SNOMED CT).

Conclusions:

  • Knowledge graph embeddings provide a computationally tractable method for analyzing complex pain concepts.
  • Integrating EHR data with standardized medical terminologies like SNOMED CT enhances pain knowledge representation.
  • This approach holds potential for improving pain understanding and modeling in clinical settings.