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A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

A modular framework for biomedical concept recognition.

David Campos¹, Sérgio Matos, José Luís Oliveira

¹IEETA/DETI, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal. david.campos@ua.pt.

BMC Bioinformatics

|September 26, 2013

Summary

This summary is machine-generated.

Neji is an open-source framework for biomedical concept recognition, offering modularity, speed, and usability. It achieves high performance in named entity recognition and entity normalization, streamlining research in the biomedical domain.

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Area of Science:

Biomedical Informatics
Computational Biology
Natural Language Processing

Background:

Biomedical concept recognition is crucial for information extraction but presents significant challenges.
Existing solutions often rely on ad-hoc methods or general frameworks not optimized for the biomedical domain.

Purpose of the Study:

To introduce Neji, an open-source framework specifically designed for efficient and accurate biomedical concept recognition.
To provide a modular, scalable, and user-friendly tool for researchers and developers.

Main Methods:

Neji integrates modules for various biomedical natural language processing tasks, including tokenization, lemmatization, and dependency parsing.
Concept recognition is achieved through dictionary matching and machine learning, incorporating normalization and disambiguation techniques.
The framework supports popular input/output formats and allows for custom module implementation.

Main Results:

Neji demonstrated high performance on named entity recognition (e.g., species 95%, disorders 85%) and entity normalization (e.g., species 88%, chemicals 53%) across three gold standard corpora.
The framework offers fast, multi-threaded processing, annotating up to 1200 sentences per second.

Conclusions:

Neji streamlines the development of complex concept recognition solutions for the biomedical community.
The open-source framework is freely available, promoting wider adoption and contribution.