Akram Redjdal

Orcid: 0000-0003-3141-5463

According to our database1, Akram Redjdal authored at least 13 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
LIMICS@DEFT'24 : Un mini-LLM peut-il tricher aux QCM de pharmacie en fouillant dans Wikipédia et NACHOS ?
Proceedings of the Actes du Défi Fouille de Textes@TALN 2024, 2024

Leveraging Rule-Based NLP to Translate Textual Reports as Structured Inputs Automatically Processed by a Clinical Decision Support System.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Exploring Explainable AI Techniques for Text Classification in Healthcare: A Scoping Review.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Measured Performance and Healthcare Professional Perception of Large Language Models Used as Clinical Decision Support Systems: A Scoping Review.
Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

2023
Clinical Decision Support Systems Applied to the Management of Breast Cancer Patients: A Scoping Review.
Proceedings of the Healthcare Transformation with Informatics and Artificial Intelligence, 2023

2022
Using Machine Learning and Deep Learning Methods to Predict the Complexity of Breast Cancer Cases.
Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Methods Used to Compare Narrative Clinical Practice Guidelines: A Scoping Review.
Proceedings of the Advances in Informatics, Management and Technology in Healthcare, 2022

2021
Reusing Decisions Made with One Decision Support System to Assess a Second Decision Support System: Introducing the Notion of Complex Cases.
Proceedings of the Public Health and Informatics, 2021

Using Machine Learning on Imbalanced Guideline Compliance Data to Optimize Multidisciplinary Tumour Board Decision Making for the Management of Breast Cancer Patients.
Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

Comparison of MetaMap, cTAKES, SIFR, and ECMT to Annotate Breast Cancer Patient Summaries.
Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

Deep Learning, a Not so Magical Problem Solver: A Case Study with Predicting the Complexity of Breast Cancer Cases.
Proceedings of the Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era, 2021

Are Semantic Annotators Able to Extract Relevant Complexity-Related Concepts from Clinical Notes?
Proceedings of the Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era, 2021

2020
Creating Synthetic Patients to Address Interoperability Issues: A Case Study with the Management of Breast Cancer Patients.
Proceedings of the Integrated Citizen Centered Digital Health and Social Care - Citizens as Data Producers and Service co-Creators, 2020


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