Quo vadis artificial intelligence?
The study of artificial intelligence (AI) has been a continuous endeavor of scientists and
engineers for over 65 years. The simple contention is that human-created machines can do …
engineers for over 65 years. The simple contention is that human-created machines can do …
[HTML][HTML] Recent advances in electrochemical biosensors: Applications, challenges, and future scope
A Singh, A Sharma, A Ahmed, AK Sundramoorthy… - Biosensors, 2021 - mdpi.com
The electrochemical biosensors are a class of biosensors which convert biological
information such as analyte concentration that is a biological recognition element …
information such as analyte concentration that is a biological recognition element …
Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRI
Brain tumor segmentation in multimodal MRI has great significance in clinical diagnosis and
treatment. The utilization of multimodal information plays a crucial role in brain tumor …
treatment. The utilization of multimodal information plays a crucial role in brain tumor …
A review of medical image data augmentation techniques for deep learning applications
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
Convolutional neural networks in medical image understanding: a survey
DR Sarvamangala, RV Kulkarni - Evolutionary intelligence, 2022 - Springer
Imaging techniques are used to capture anomalies of the human body. The captured images
must be understood for diagnosis, prognosis and treatment planning of the anomalies …
must be understood for diagnosis, prognosis and treatment planning of the anomalies …
Image segmentation for MR brain tumor detection using machine learning: a review
Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
A comprehensive survey of recent trends in deep learning for digital images augmentation
Deep learning proved its efficiency in many fields of computer science such as computer
vision, image classifications, object detection, image segmentation, and more. Deep …
vision, image classifications, object detection, image segmentation, and more. Deep …
MRI-based brain tumor classification using ensemble of deep features and machine learning classifiers
Brain tumor classification plays an important role in clinical diagnosis and effective
treatment. In this work, we propose a method for brain tumor classification using an …
treatment. In this work, we propose a method for brain tumor classification using an …
Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
Advancing biosensors with machine learning
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis.
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …