A5064263884- Brain Tumor Detection and Classification
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Glioma Diagnosis and Treatment
- Remote-Sensing Image Classification
- MRI in cancer diagnosis
- Peer-to-Peer Network Technologies
- Digital Imaging for Blood Diseases
- Opinion Dynamics and Social Influence
- Digital Radiography and Breast Imaging
- Digital Mental Health Interventions
- Optical Imaging and Spectroscopy Techniques
- Time Series Analysis and Forecasting
- Music and Audio Processing
- Complex Network Analysis Techniques
- Suicide and Self-Harm Studies
- Cellular Automata and Applications
- Infrared Thermography in Medicine
- Advanced Neural Network Applications
- Psychopathy, Forensic Psychiatry, Sexual Offending
- graph theory and CDMA systems
- Speech Recognition and Synthesis
- Coding theory and cryptography
Atlantic Technological University
2022-2023
Technological University Dublin
2022-2023
Galway-Mayo Institute of Technology
2021
Ollscoil na Gaillimhe – University of Galway
2011
In this paper we cluster and analyse temporal user behaviour in online communities. We adapt a simple unsupervised clustering algorithm to an evolutionary setting where users into prototypical behavioural roles based on features derived from their ego-centric reply-graphs. then changes the role membership of over time, change composition forums time examine differences between terms composition. perform analysis 200 popular national bulletin board 14 enterprise technical support forums.
The identification of glioblastoma progression from the non-contrast enhancing areas is critically challenging to clinicians. This leads poor prognosis and a very high local rate even after surgical resection chemo-radiotherapy. Deep learning methods have been aiding in tracking tumor segmentation progression. However, feature-based these requires large datasets, multiple annotations, measurements, resulting complex, time-consuming networks. work introduces random Graph Neural Network (GNN)...
Motivation: Diagnosis and grading of astrocytomas tumour present considerable challenges. Manual is time-consuming error prone. Preoperative MRIs are a useful, yet deep learning presents challenges due to computing limitations complex architecture. Goal(s): Study introduces novel multimodal MRI classification for grade II III astrocytomas, aiming improve accuracy, reduce complexity, address interclass homogeneity via attention mechanism. Approach: Single slice from eight modalities forms...
Glioblastoma (GB) is a malignant brain tumor and requires surgical resection. Although complete resection of GB improves prognosis, supratotal may cause neurological abnormalities. Therefore, intraoperative tissue classification techniques are needed to delineate infected regions remove reoccurrences. To the affected regions, surgeons mostly rely on traditional magnetic resonance imaging (MRI) which often lacks accuracy precision due brain-shift phenomenon. Hyperspectral Imaging (HSI)...