Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Combination Therapies and Personalized Medicine

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...

Targeted Cancer Therapies

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Innovative diabetes mellitus treatment strategies: Mesenchymal stem cell-based therapy and its impact on pro- and anti-inflammatory cytokines modulation.

Journal of pharmaceutical analysis·2026

Same author

Augmenting large language models with clinical knowledge graph for personalized perioperative fluid therapy question answering.

PLOS digital health·2026

Same author

Modulating the Gut-Liver Axis: Anti-Inflammatory Mechanisms of Probiotics and Prebiotics in MASLD.

Probiotics and antimicrobial proteins·2026

Same author

PEPRKD-depression: A knowledge database supporting evidence-based personalized exercise prescription recommendations in depression.

Digital health·2026

Same author

Benchmarking Large Language Models and Prompt Engineering Strategies in Microsatellite Instability Cancers: Evaluation Study.

Journal of medical Internet research·2026

Same author

Future landscapes of women's hormone-sensitive cancers: unraveling global trends, age stratification, and regional inequities (1990-2035).

Frontiers in endocrinology·2026

Same journal

Evaluation of temporal preservation in synthetic longitudinal patient data.

Journal of biomedical informatics·2026

Same journal

ARKE: An ontology-driven framework for automated mapping of local radiology procedure terms to the LOINC-RadLex playbook using large language model.

Journal of biomedical informatics·2026

Same journal

A validation-driven training controller for cross-lingual biomedical NER via reinforcement learning-based adaptive loss weighting.

Journal of biomedical informatics·2026

Same journal

ASP-HR: An Adaptive Spatial Perception and Hierarchical Reasoning mechanism for document-level biomedical relation extraction.

Journal of biomedical informatics·2026

Same journal

Beyond Accuracy: Safety-Centered guidelines for the evaluation of LLM-based therapy recommendation systems for chronic multimorbidity patients.

Journal of biomedical informatics·2026

Same journal

DeepEN: A deep reinforcement learning framework for personalized enteral nutrition in critical care.

Journal of biomedical informatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 15, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Advancing Chinese biomedical text mining with community challenges.

Hui Zong¹, Rongrong Wu¹, Jiaxue Cha²

¹Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610041, China.

Journal of Biomedical Informatics

|August 28, 2024

Summary

This summary is machine-generated.

Community challenges in biomedical text mining in China have advanced technology and collaboration. These 39 evaluation tasks (2017-2023) cover diverse natural language processing applications, driving innovation in biomedical informatics.

Keywords:

Artificial intelligence Biomedical text mining Health information processing Large language model Natural language processing

More Related Videos

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Related Experiment Videos

Last Updated: Jun 15, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

Biomedical informatics
Natural Language Processing
Computational Linguistics

Background:

Biomedical text mining is crucial for extracting knowledge from vast amounts of literature.
Community challenges serve as vital platforms for evaluating and advancing text mining techniques.
Recent years have seen significant growth in biomedical text mining initiatives in China.

Purpose of the Study:

To review recent advances in community challenges for biomedical text mining in China.
To systematically analyze the landscape of evaluation tasks and datasets.
To explore the clinical applications and future directions of these challenges.

Main Methods:

Information on evaluation tasks from community challenges was collected, including descriptions, datasets, and task types.
A systematic summary and comparative analysis of various biomedical natural language processing tasks were performed.
Tasks included named entity recognition, relation extraction, text classification, and large language model evaluation.

Main Results:

39 evaluation tasks from 6 community challenges (2017-2023) were identified.
Analysis revealed diverse task types and data sources, with potential clinical applications.
Comparison with English counterparts and discussion of contributions, limitations, and future directions were conducted.

Conclusions:

Community challenge evaluation competitions significantly promote technological innovation in biomedical text mining.
These challenges foster interdisciplinary collaboration and provide platforms for developing state-of-the-art solutions.
They are instrumental in advancing the field, especially with the rise of large language models.