Posts’ Archive


2024

To Automate or To Augment Humans? That is the Question for AI, and The Answer Depends on Users’ Requirements

May 2, 2024

The growing influence of AI brings benefits and risks. Our research explores how human-centred AI balances automation and human control in website usability evaluation. It shows how AI streamlines the detection of critical usability issues while augmented approaches also uncover less severe issues.

Detecting Brain Tumors through Multi-modal AI Models

March 11, 2024

Brain tumors are tricky to diagnose and treat due to the brain’s complexity. Detecting them quickly improves patient chances. Our study explores using Artificial Intelligence (AI), specifically deep learning, to save time and resources in finding tumors from imaging. We tested an AI model on MRI scans and achieved about 99% accuracy. We also emphasize the importance of explaining and being transparent about how the AI works to ensure human control and safety in the diagnostic process.

The Future of Alzheimer’s Diagnosis: Unlocking Insights with Multi-modal Imaging Models

March 3, 2024

Dementia affects ~55 million individuals worldwide, with Alzheimer’s disease (AD) being the predominant type. Artificial Intelligence (AI) may aid in its diagnosis. We propose and evaluate multi-modal models for the task, incorporating eXplainable Artificial Intelligence for diagnostic transparency.

2023

My Thoughts on the Evolution of AI Research

October 18, 2023

Artificial Intelligence (AI) has been making significant strides in recent years, thanks to the advent of Deep Learning algorithms and the rise of large-scale datasets. The powerful impact of such models is, to use a euphemism, extremely exciting for a young researcher like me. However, I have to admit I am becoming increasingly worried about the impact that these models have.