A Critical Review of Artificial Intelligence Based Approaches in Intrusion Detection: A Comprehensive Analysis
Intrusion detection (ID) is critical in securing computer networks against various malicious
attacks. Recent advancements in machine learning (ML), deep learning (DL), federated …
attacks. Recent advancements in machine learning (ML), deep learning (DL), federated …
[PDF][PDF] Cross project software defect prediction using machine learning: a review
MS Saeed, M Saleem - International Journal of Computational …, 2023 - researchgate.net
Software defect prediction is a crucial area of study focused on enhancing software quality
and cutting down on software upkeep expenses. Cross Project Defect Prediction (CPDP) is …
and cutting down on software upkeep expenses. Cross Project Defect Prediction (CPDP) is …
Utilizing customized CNN for brain tumor prediction with explainable AI
Timely diagnosis of brain tumors using MRI and its potential impact on patient survival are
critical issues addressed in this study. Traditional DL models often lack transparency …
critical issues addressed in this study. Traditional DL models often lack transparency …
An XAI-enhanced efficientNetB0 framework for precision brain tumor detection in MRI imaging
Background Accurately diagnosing brain tumors from MRI scans is crucial for effective
treatment planning. While traditional methods heavily rely on radiologist expertise, the …
treatment planning. While traditional methods heavily rely on radiologist expertise, the …
[HTML][HTML] Enhancing deep learning model Explainability in brain tumor datasets using post-heuristic approaches
K Pasvantis, E Protopapadakis - Journal of Imaging, 2024 - mdpi.com
The application of deep learning models in medical diagnosis has showcased considerable
efficacy in recent years. Nevertheless, a notable limitation involves the inherent lack of …
efficacy in recent years. Nevertheless, a notable limitation involves the inherent lack of …
Optimized brain tumor identification via graph sample and aggregate-attention network with Artificial Lizard Search Algorithm
A brain tumour is an abnormal growth of brain nerves that interferes with normal brain
function. It causes a great deal of deaths. Timely detection and treatment are essential for …
function. It causes a great deal of deaths. Timely detection and treatment are essential for …
[HTML][HTML] Explainable AI in Diagnostic Radiology for Neurological Disorders: A Systematic Review, and What Doctors Think About It
Background: Artificial intelligence (AI) has recently made unprecedented contributions in
every walk of life, but it has not been able to work its way into diagnostic medicine and …
every walk of life, but it has not been able to work its way into diagnostic medicine and …
[PDF][PDF] Harnessing Machine Learning Techniques for Intelligent Disease Prediction
MI Asghar, F Ahmed, S Khan - International Journal of …, 2023 - researchgate.net
Anemia, a prevalent medical illness characterized by a deficiency in red blood cells or
hemoglobin, remains a substantial global health issue. The significance of timely …
hemoglobin, remains a substantial global health issue. The significance of timely …
An XAI-infused multiclass MRI brain tumor classification using deep transfert learning (DTL)
H Charaabi, A Sayari, R El Hamdi… - … on Control, Decision …, 2024 - ieeexplore.ieee.org
This study underscores the critical role of accurately classifying brain tumors in Magnetic
Resonance Imaging (MRI) for clinical diagnosis and treatment planning. Deep Transfer …
Resonance Imaging (MRI) for clinical diagnosis and treatment planning. Deep Transfer …
A framework for identification of brain tumors from MR images using progressive segmentation
Purpose This study addresses the critical health issue of brain tumors, focusing on
enhancing the accuracy of tumor segmentation from Magnetic Resonance Imaging (MRI) …
enhancing the accuracy of tumor segmentation from Magnetic Resonance Imaging (MRI) …