6 citations · 8 across the 8 of their papers we have counts for
8 papers
CaresAI at SMM4H-HeaRD 2026: Predicting TNM Staging
Joseph Itopa Abubakar, Jorge Jarme, Favour Igwezeke +1
This study aims to predict Tumor, Node, and Metastasis (TNM) stage labels independently, with the Cancer Genome Atlas (TCGA) pathology report as the sixth shared task of SMM4H-HeaR…
CaresAI at CT-DEB26: Detecting Dosing Errors In Clinical Trials Using Domain-Specific Transformer Embeddings and Classification Models
Leon Hamnett, Favour Igwezeke, Joseph Itopa Abubakar +1
Medication errors, particularly dosing errors in clinical trials (CT), can lead to patient harm, adverse drug events and worse patient outcomes. Dosing errors are preventable, and…
CaresAI at BioCreative IX Track 1 -- LLM for Biomedical QA
Reem Abdel-Salam, Mary Adewunmi, Modinat A. Abayomi
Large language models (LLMs) are increasingly evident for accurate question answering across various domains. However, rigorous evaluation of their performance on complex question-…
Enhancing Health Mention Classification Performance: A Study on Advancements in Parameter Efficient Tuning
Reem Abdel-Salam, Mary Adewunmi
Health Mention Classification (HMC) plays a critical role in leveraging social media posts for real-time tracking and public health monitoring. Nevertheless, the process of HMC pre…
PubTrend: General Overview of Artificial Intelligence for Colorectal cancer diagnosis from 2010-2022
Mary Adewunmi, Reem Abdel-Salam
Colorectal cancer (CRC) is among the most prevalent cancers in the world. Due to numerous scholarly papers and broad enquiries about specific use cases for artificial intelligence…
Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques
Leon Hamnett, Mary Adewunmi, Modinat Abayomi +2
Breast cancer remains a critical global health challenge, necessitating early and accurate detection for effective treatment. This paper introduces a methodology that combines auto…
Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images
Fahad Ahmed, Reem Abdel-Salam, Leon Hamnett +2
Breast cancer is one of the leading causes of death for women worldwide. Early screening is essential for early identification, but the chance of survival declines as the cancer pr…
Artificial intelligence based prediction on lung cancer risk factors using deep learning
Muhammad Sohaib, Mary Adewunmi
In this proposed work, we identified the significant research issues on lung cancer risk factors. Capturing and defining symptoms at an early stage is one of the most difficult pha…