Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a sco** review

C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …

Vision transformer architecture and applications in digital health: a tutorial and survey

K Al-Hammuri, F Gebali, A Kanan… - Visual computing for …, 2023 - Springer
The vision transformer (ViT) is a state-of-the-art architecture for image recognition tasks that
plays an important role in digital health applications. Medical images account for 90% of the …

A novel Swin transformer approach utilizing residual multi-layer perceptron for diagnosing brain tumors in MRI images

I Pacal - International Journal of Machine Learning and …, 2024 - Springer
Serious consequences due to brain tumors necessitate a timely and accurate diagnosis.
However, obstacles such as suboptimal imaging quality, issues with data integrity, varying …

Brain tumor detection and multi-grade segmentation through hybrid caps-VGGNet model

A Jabbar, S Naseem, T Mahmood, T Saba… - IEEE …, 2023 - ieeexplore.ieee.org
Around the world, brain tumors are becoming the leading cause of mortality. The inability to
undertake a timely tumor diagnosis is the primary cause of this pandemic. Brain cancer …

Artificial intelligence in brain tumor imaging: a step toward personalized medicine

M Cè, G Irmici, C Foschini, GM Danesini, LV Falsitta… - Current …, 2023 - mdpi.com
The application of artificial intelligence (AI) is accelerating the paradigm shift towards patient-
tailored brain tumor management, achieving optimal onco-functional balance for each …

Advancements and prospects of machine learning in medical diagnostics: unveiling the future of diagnostic precision

S Asif, Y Wenhui, S ur-Rehman, Q ul-ain… - … Methods in Engineering, 2024 - Springer
Abstract Machine learning (ML) has emerged as a versatile and powerful tool in various
fields of medicine, revolutionizing early disease diagnosis, particularly in cases where …

Brain tumor detection and screening using artificial intelligence techniques: Current trends and future perspectives

U Raghavendra, A Gudigar, A Paul, TS Goutham… - Computers in Biology …, 2023 - Elsevier
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 …

[HTML][HTML] An augmented modulated deep learning based intelligent predictive model for brain tumor detection using GAN ensemble

S Sahoo, S Mishra, B Panda, AK Bhoi, P Barsocchi - Sensors, 2023 - mdpi.com
Brain tumor detection in the initial stage is becoming an intricate task for clinicians
worldwide. The diagnosis of brain tumor patients is rigorous in the later stages, which is a …

An effective and novel approach for brain tumor classification using AlexNet CNN feature extractor and multiple eminent machine learning classifiers in MRIs

A Sarkar, M Maniruzzaman, MA Alahe… - Journal of …, 2023 - Wiley Online Library
A brain tumor is an uncontrolled malignant cell growth in the brain, which is denoted as one
of the deadliest types of cancer in people of all ages. Early detection of brain tumors is …

Attention transformer mechanism and fusion-based deep learning architecture for MRI brain tumor classification system

S Tabatabaei, K Rezaee, M Zhu - Biomedical Signal Processing and …, 2023 - Elsevier
Most primary brain malignancies are malignant tumors characterized by masses of
abnormal tissue that grow uncontrollably. Recently, deep transfer learning (DTL) has been …