The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)*** study introduces Dynamic GradNet,a novel deep learning model design...
详细信息
The evolving field of Alzheimer’s disease(AD)diagnosis has greatly benefited from deep learning models for analyzing brain magnetic resonance(MR)*** study introduces Dynamic GradNet,a novel deep learning model designed to increase diagnostic accuracy and interpretability for multiclass AD ***,four state-of-the-art convolutional neural network(CNN)architectures,the self-regulated network(RegNet),residual network(ResNet),densely connected convolutional network(DenseNet),and efficient network(EfficientNet),were comprehensively compared via a unified preprocessing pipeline to ensure a fair *** these models,EfficientNet consistently demonstrated superior performance in terms of accuracy,precision,recall,and F1 *** a result,EfficientNetwas selected as the foundation for implementing Dynamic *** GradNet incorporates gradient weighted class activation mapping(GradCAM)into the training process,facilitating dynamic adjustments that focus on critical brain regions associated with early dementia *** adjustments are particularly effective in identifying subtle changes associated with very mild dementia,enabling early diagnosis and *** model was evaluated with the OASIS dataset,which contains greater than 80,000 brain MR images categorized into four distinct stages of AD *** proposed model outperformed the baseline architectures,achieving remarkable generalizability across all *** findingwas especially evident in early-stage dementia detection,where Dynamic GradNet significantly reduced false positives and enhanced classification *** findings highlight the potential of Dynamic GradNet as a robust and scalable approach for AD diagnosis,providing a promising alternative to traditional attention-based *** model’s ability to dynamically adjust spatial focus offers a powerful tool in artificial intelligence(AI)assisted precisionmedicine,particularly in the early det
Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of ***,both deep learning and ensemble learni...
详细信息
Deep learning algorithms have been rapidly incorporated into many different applications due to the increase in computational power and the availability of massive amounts of ***,both deep learning and ensemble learning have been used to recognize underlying structures and patterns from high-level features to make predictions/*** the growth in popularity of deep learning and ensemble learning algorithms,they have received significant attention from both scientists and the industrial community due to their superior ability to learn features from big *** deep learning has exhibited significant performance in enhancing learning generalization through the use of multiple deep learning *** ensemble deep learning has large quantities of training parameters,which results in time and space overheads,it performs much better than traditional ensemble *** deep learning has been successfully used in several areas,such as bioinformatics,finance,and health *** this paper,we review and investigate recent ensemble deep learning algorithms and techniques in health care domains,medical imaging,health care data analytics,genomics,diagnosis,disease prevention,and drug *** cover several widely used deep learning algorithms along with their architectures,including deep neural networks(DNNs),convolutional neural networks(CNNs),recurrent neural networks(RNNs),and generative adversarial networks(GANs).Common healthcare tasks,such as medical imaging,electronic health records,and genomics,are also ***,in this review,the challenges inherent in reducing the burden on the healthcare system are discussed and ***,future directions and opportunities for enhancing healthcare model performance are discussed.
Multi-exposure image fusion (MEF) involves combining images captured at different exposure levels to create a single, well-exposed fused image. MEF has a wide range of applications, including low light, low contrast, ...
详细信息
The Internet of Things (IoT) has developed into a crucial component for meeting the connection needs of the current smart healthcare systems. The Internet of Medical Things (IoMT) consists of medical devices that are ...
详细信息
Aspect-based sentiment analysis (ABSA) is a natural language processing (NLP) technique to determine the various sentiments of a customer in a single comment regarding different aspects. The increasing online data con...
详细信息
Delay tolerant wireless sensor networks(DTWSN)is a class of wireless network that finds its deployment in those application scenarios which demand for high packet delivery ratio while maintaining minimal overhead in o...
详细信息
Delay tolerant wireless sensor networks(DTWSN)is a class of wireless network that finds its deployment in those application scenarios which demand for high packet delivery ratio while maintaining minimal overhead in order to prolong network lifetime;owing to resource-constrained nature of *** fundamental requirement of any network is routing a packet from its source to *** of a routing algorithm depends on the number of network parameters utilized by that routing *** the recent years,various routing protocol has been developed for the delay tolerant networks(DTN).A routing protocol known as spray and wait(SnW)is one of the most widely used routing algorithms for *** this paper,we study the SnW routing protocol and propose a modified version of it referred to as Pentago SnW which is based on pentagonal number *** to binary SnW shows promising results through simulation using real-life scenarios of cars and pedestrians randomly moving on a map.
ASR is an effectual approach, which converts human speech into computer actions or text format. It involves extracting and determining the noise feature, the audio model, and the language model. The extraction and det...
详细信息
The k-Nearest Neighbors (kNN) algorithm is one of the most widely used techniques for data classification. However, the imbalanced class is a key problem for its declining performance. Therefore, the kNN algorithm is ...
详细信息
Sequence-to-sequence models are fundamental building blocks for generating abstractive text summaries, which can produce precise and coherent summaries. Recently proposed, different text summarization models aimed to ...
详细信息
This systematic review gave special attention to diabetes and the advancements in food and nutrition needed to prevent or manage diabetes in all its forms. There are two main forms of diabetes mellitus: Type 1 (T1D) a...
详细信息
暂无评论