A systematic literature review of neuroimaging coupled with machine learning approaches for diagnosis of attention deficit hyperactivity disorder
I Ashraf, S Jung, S Hur, Y Park - Journal of Big Data, 2024 - Springer
Problem Attention deficit hyperactivity disorder (ADHD) is the most commonly found
neurodevelopmental condition among children with an estimated 2.5% to 9% global …
neurodevelopmental condition among children with an estimated 2.5% to 9% global …
White blood cells classification using multi-fold pre-processing and optimized CNN model
White blood cells (WBCs) play a vital role in immune responses against infections and
foreign agents. Different WBC types exist, and anomalies within them can indicate diseases …
foreign agents. Different WBC types exist, and anomalies within them can indicate diseases …
A robust approach for multi-type classification of brain tumor using deep feature fusion
W Chen, X Tan, J Zhang, G Du, Q Fu… - Frontiers in …, 2024 - frontiersin.org
Brain tumors can be classified into many different types based on their shape, texture, and
location. Accurate diagnosis of brain tumor types can help doctors to develop appropriate …
location. Accurate diagnosis of brain tumor types can help doctors to develop appropriate …
Enhanced MRI-based brain tumour classification with a novel Pix2pix generative adversarial network augmentation framework
EP Onakpojeruo, MT Mustapha… - Brain …, 2024 - academic.oup.com
The scarcity of medical imaging datasets and privacy concerns pose significant challenges
in artificial intelligence-based disease prediction. This poses major concerns to patient …
in artificial intelligence-based disease prediction. This poses major concerns to patient …
An improved skin lesion detection solution using multi-step preprocessing features and NASNet transfer learning model
Computer-aided diagnosis has shown its potential for accurate detection of various diseases
like skin lesion. Skin lesion has been recognized as a challenging task since manual …
like skin lesion. Skin lesion has been recognized as a challenging task since manual …
Brain Tumor Recognition Using Artificial Intelligence Neural-Networks (BRAIN): A Cost-Effective Clean-Energy Platform
Brain tumors necessitate swift detection and classification for optimal patient outcomes.
Deep learning has been extensively utilized to recognize complex tumor patterns in …
Deep learning has been extensively utilized to recognize complex tumor patterns in …
Brain tumor detection using 3D-UNet segmentation features and hybrid machine learning model
Machine learning has significantly improved disease diagnosis, enhancing the efficiency
and accuracy of the healthcare system. One critical area where it proves beneficial is …
and accuracy of the healthcare system. One critical area where it proves beneficial is …
Transfer learning based approach for lung and colon cancer detection using local binary pattern features and explainable artificial intelligence (AI) techniques
S Alsubai - PeerJ Computer Science, 2024 - peerj.com
Cancer, a life-threatening disorder caused by genetic abnormalities and metabolic
irregularities, is a substantial health danger, with lung and colon cancer being major …
irregularities, is a substantial health danger, with lung and colon cancer being major …
Novel approach for Arabic fake news classification using embedding from large language features with CNN-LSTM ensemble model and explainable AI
O Ibrahim Aboulola, M Umer - Scientific Reports, 2024 - nature.com
The widespread fake news challenges the management of low-quality information, making
effective detection strategies necessary. This study addresses this critical issue by …
effective detection strategies necessary. This study addresses this critical issue by …
Hepatocellular carcinoma recognition from ultrasound images by fusing convolutional neural networks at decision level
The Hepatocellular Carcinoma (HCC) is the most often met malignant tumor of the liver. It
develops from cirrhosis, after a parenchyma restructuring phase, at the end of which …
develops from cirrhosis, after a parenchyma restructuring phase, at the end of which …