Related Experiment Video
Updated: Jan 29, 2026
08:20
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
Published on: October 27, 2023
2.5K
Accurate Clinical Entity Recognition and Code Mapping of Anatomopathological Reports Using BioClinicalBERT Enhanced
Hamida Abdaoui1, Chamseddine Barki1, Ismail Dergaa2
1Laboratory of Biophysics and Medical Technologies, Higher Institute of Medical Technologies of Tunis (ISTMT), University of Tunis El Manar, Tunis 1006, Tunisia.
Bioengineering (Basel, Switzerland)
|January 28, 2026
Summary
This study presents an automated pipeline for extracting and standardizing information from anatomopathological reports, improving data accessibility for research. The system demonstrates high accuracy in entity recognition and multi-ontology normalization, overcoming limitations of manual data processing.
Area of Science:
- Medical Informatics
- Natural Language Processing
- Computational Pathology
Background:
- Anatomopathological reports are unstructured, hindering automated data extraction and large-scale research.
- Manual data standardization is resource-intensive and difficult to scale.
Purpose of the Study:
- To develop and evaluate an automated pipeline for entity extraction and multi-ontology normalization of anatomopathological reports.
- To enhance data interoperability and facilitate automated research using clinical text.
Main Methods:
- A corpus of 560 reports was annotated for sample type, test performed, and finding.
- Entity extraction employed BioBERT v1.1.
- Normalization utilized BioClinicalBERT with retrieval-augmented generation over SNOMED CT, LOINC, and ICD-11.
Main Results:
- High extraction performance achieved (overall F1-score of 0.963).
- The combined BioClinicalBERT and dense retrieval approach outperformed others for terminology mapping.
- Substantial to near-perfect agreement (Cohen's Kappa 0.7829-0.9773) demonstrated robust coding.
Conclusions:
- The developed pipeline offers robust automated extraction and multi-ontology coding for anatomopathological entities.
- Transformer-based named entity recognition and retrieval-augmented generation support the system's capabilities.
- Multi-institutional validation is recommended prior to clinical deployment due to study limitations.
Keywords:
BioClinicalBERTICD-11LOINCSNOMED CTanatomopathological reportcode mappingdeep learningnamed entity recognitionnatural language processingtransformer architectureMore Related Videos
Related Concept Videos
01:12Retrieval
438
Retrieval is the process of getting information out of memory storage and back into conscious awareness. This ability is essential for daily tasks like brushing hair and teeth, driving to work, and performing job duties. Retrieval occurs in three ways: recall, recognition, and relearning.
Recall involves accessing information without cues, such as during an essay test, where individuals must retrieve facts and concepts from memory unaided. Another example is remembering the name of a colleague...
Recall involves accessing information without cues, such as during an essay test, where individuals must retrieve facts and concepts from memory unaided. Another example is remembering the name of a colleague...
438
02:39lncRNA - Long Non-coding RNAs
9.9K
In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA...
9.9K
03:00Self-Evaluation: Self-Enhancement and Self-Verification
5.8K
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
5.8K
01:45ER Retrieval Pathway
4.8K
In the secretory pathway, vesicles transport proteins from one cellular compartment to another in forward transport to deliver the protein to its correct location. Occasionally, misfolded proteins and incorrect proteins escape their original compartments, and a retrieval pathway is used to return the escaped proteins to their original compartment.
The ER uses many checkpoints to prevent the entry of incorrectly folded or a resident protein as cargo onto a transport vesicle. These mechanisms...
The ER uses many checkpoints to prevent the entry of incorrectly folded or a resident protein as cargo onto a transport vesicle. These mechanisms...
4.8K
03:24Hybridization of Atomic Orbitals I
66.7K
The mathematical expression known as the wave function, ψ, contains information about each orbital and the wavelike properties of electrons in an isolated atom. When atoms are bound together in a molecule, the wave functions combine to produce new mathematical descriptions that have different shapes. This process of combining the wave functions for atomic orbitals is called hybridization and is mathematically accomplished by the linear combination of atomic orbitals. The new orbitals that...
66.7K
02:29Hybrid Zones
21.8K
Hybrid zones are narrow regions where two closely related species interact, mate, and produce hybrids. Relative to either parent species, hybrids may possess distinct phenotypic or genetic differences that impact their survival and reproductive success. The genetic variances introduced by hybridization influence species diversity and speciation processes within the hybrid zone.
21.8K