The role of artificial intelligence in early cancer diagnosis
B Hunter, S Hindocha, RW Lee - Cancers, 2022 - mdpi.com
Simple Summary Diagnosing cancer at an early stage increases the chance of performing
effective treatment in many tumour groups. Key approaches include screening patients who …
effective treatment in many tumour groups. Key approaches include screening patients who …
Deep learning for computational cytology: A survey
Computational cytology is a critical, rapid-develo**, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …
image computing concerned with analyzing digitized cytology images by computer-aided …
Quantum Fruit Fly algorithm and ResNet50-VGG16 for medical diagnosis
Medical data are present in large amount and this is difficult to process for the diagnosis and
Healthcare organization requires effective technique to handle big data. Existing techniques …
Healthcare organization requires effective technique to handle big data. Existing techniques …
Deep embedded median clustering for routing misbehaviour and attacks detection in ad-hoc networks
A Rajendran, N Balakrishnan, P Ajay - Ad Hoc Networks, 2022 - Elsevier
Due to the properties of ad-hoc networks, it appears that designing sophisticated defence
schemes with more computing capital is impossible in most situations. Recently, an …
schemes with more computing capital is impossible in most situations. Recently, an …
Deep semi-supervised multiple instance learning with self-correction for DME classification from OCT images
Supervised deep learning has achieved prominent success in various diabetic macular
edema (DME) recognition tasks from optical coherence tomography (OCT) volumetric …
edema (DME) recognition tasks from optical coherence tomography (OCT) volumetric …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Pfemed: Few-shot medical image classification using prior guided feature enhancement
Deep learning-based methods have recently demonstrated outstanding performance on
general image classification tasks. As optimization of these methods is dependent on a large …
general image classification tasks. As optimization of these methods is dependent on a large …
Dual-consistency semi-supervised learning with uncertainty quantification for COVID-19 lesion segmentation from CT images
The novel coronavirus disease 2019 (COVID-19) characterized by atypical pneumonia has
caused millions of deaths worldwide. Automatically segmenting lesions from chest …
caused millions of deaths worldwide. Automatically segmenting lesions from chest …
Image quality-aware diagnosis via meta-knowledge co-embedding
Medical images usually suffer from image degradation in clinical practice, leading to
decreased performance of deep learning-based models. To resolve this problem, most …
decreased performance of deep learning-based models. To resolve this problem, most …
Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis
H **ang, J Shen, Q Yan, M Xu, X Shi, X Zhu - Medical Image Analysis, 2023 - Elsevier
Recently, convolutional neural networks (CNNs) directly using whole slide images (WSIs) for
tumor diagnosis and analysis have attracted considerable attention, because they only …
tumor diagnosis and analysis have attracted considerable attention, because they only …