Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives
A brain tumor is an abnormal mass of tissue located inside the skull. In addition to putting
pressure on the healthy parts of the brain, it can lead to significant health problems …
pressure on the healthy parts of the brain, it can lead to significant health problems …
[HTML][HTML] Efficient U-Net architecture with multiple encoders and attention mechanism decoders for brain tumor segmentation
The brain is the center of human control and communication. Hence, it is very important to
protect it and provide ideal conditions for it to function. Brain cancer remains one of the …
protect it and provide ideal conditions for it to function. Brain cancer remains one of the …
Interpretable machine learning model to predict survival days of malignant brain tumor patients
An artificial intelligence (AI) model's performance is strongly influenced by the input features.
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …
[HTML][HTML] 3DUV-NetR+: A 3D hybrid semantic architecture using transformers for brain tumor segmentation with MultiModal MR images
Brain tumor segmentation plays a substantial role in Medical Image Analysis (MIS). In this
regard, automatic segmentation methods facilitate precise and efficient segmentation …
regard, automatic segmentation methods facilitate precise and efficient segmentation …
[HTML][HTML] Artificial intelligence approach for early detection of brain tumors using MRI images
Artificial intelligence (AI) is one of the most promising approaches to health innovation. The
use of AI in image recognition considerably extends findings beyond the constraints of …
use of AI in image recognition considerably extends findings beyond the constraints of …
Inception-UDet: an improved U-Net architecture for brain tumor segmentation
Brain tumor segmentation is an important field and a sensitive task in tumor diagnosis. The
treatment research in this area has helped specialists in detecting the tumor's location in …
treatment research in this area has helped specialists in detecting the tumor's location in …
Detection and classification of diabetic retinopathy using artificial intelligence algorithms
D Rahhal, R Alhamouri, I Albataineh… - … on Information and …, 2022 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is considered as a sight-threatening complication of diabetes
mellitus, the primary cause of blindness among working-age individuals. Ophthalmologists …
mellitus, the primary cause of blindness among working-age individuals. Ophthalmologists …
RU-Net2+: A deep learning algorithm for accurate brain tumor segmentation and survival rate prediction
R Zaitoon, H Syed - IEEE Access, 2023 - ieeexplore.ieee.org
Brain tumors present a significant medical concern, posing challenges in both diagnosis and
treatment. Deep learning has emerged as an evolving technique for automating the …
treatment. Deep learning has emerged as an evolving technique for automating the …
[HTML][HTML] A denoising and fourier transformation-based spectrograms in ECG classification using convolutional neural network
The non-invasive electrocardiogram (ECG) signals are useful in heart condition assessment
and are found helpful in diagnosing cardiac diseases. However, traditional ways, ie, a …
and are found helpful in diagnosing cardiac diseases. However, traditional ways, ie, a …
A hybrid deep learning approach for detection and segmentation of ovarian tumours
In recent days, artificial intelligence (AI) is gaining worldwide popularity in several industries
among which healthcare is an important sector. AI is being used in healthcare to reduce …
among which healthcare is an important sector. AI is being used in healthcare to reduce …