Leveraging Artificial Intelligence for Improved Hematologic Cancer Care: Early Diagnosis and Complications’ Prediction

Yousra El Alaoui, Regina Padmanabhan, Adel Elomri, Halima El Omri, Abdelfatteh El Omri

2024

Abstract

Today, medical artificial intelligence (AI) applications are being extensively utilized to enhance the outcomes of clinical diagnosis and overall patient care. This data-driven approach can be trained to account for individuals’ unique characteristics, medical history, ethnicity, and even genetic make-up to obtain accurately tailored treatment recommendations. Given the power of medical AI, the severe nature of hematological malignancies and the related constraints in terms of both time and cost, in this paper, we are investigating the importance of AI applications in hematology management, with an illustration of AI’s role in reducing pre-and post-diagnosis challenges. Insights discussed here are derived based on our experiments on clinical datasets from National Center for Cancer Care & Research (NCCCR), Qatar. Specifically, we developed AI models for blood cancer diagnosis as well as prediction of therapy-induced clinical complications in patients with hematological cancers to facilitate better hospital management and improved cancer care.

Paper Citation

in Harvard Style

El Alaoui Y., Padmanabhan R., Elomri A., El Omri H. and El Omri A. (2024). Leveraging Artificial Intelligence for Improved Hematologic Cancer Care: Early Diagnosis and Complications’ Prediction. In Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF; ISBN 978-989-758-688-0, SciTePress, pages 87-90. DOI: 10.5220/0012360900003657

in Bibtex Style

@conference{healthinf24,
author={Yousra El Alaoui and Regina Padmanabhan and Adel Elomri and Halima El Omri and Abdelfatteh El Omri},
title={Leveraging Artificial Intelligence for Improved Hematologic Cancer Care: Early Diagnosis and Complications’ Prediction},
booktitle={Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF},
year={2024},
pages={87-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012360900003657},
isbn={978-989-758-688-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: HEALTHINF
TI - Leveraging Artificial Intelligence for Improved Hematologic Cancer Care: Early Diagnosis and Complications’ Prediction
SN - 978-989-758-688-0
AU - El Alaoui Y.
AU - Padmanabhan R.
AU - Elomri A.
AU - El Omri H.
AU - El Omri A.
PY - 2024
SP - 87
EP - 90
DO - 10.5220/0012360900003657
PB - SciTePress