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New Methods for the Acoustic-Signal Segmentation of the Temporomandibular Joint

Marcin Kajor, Dariusz Kucharski, Justyna Grochala, Jolanta E. Loster
2022 Journal of Clinical Medicine  
The second method takes advantage of a deep learning approach established on a U-Net neural network, combined with long short-term memory (LSTM) architecture. (3) Results: Both developed methods were validated  ...  algorithms. (2) Methods: In this paper, we compare two different methods for the segmentation of TMJ sounds which are used in diagnosis of the masticatory system.  ...  Segmentation constitutes a separate step in the processing chain. Figure 1 . 1 Figure 1. Generic pipeline for heart sounds classification [7]. Figure 1 . 1 Figure 1.  ... 
doi:10.3390/jcm11102706 fatcat:bhqeet4msfaofdispzexf4ah5i

Cancer Diagnosis Using Deep Learning: A Bibliographic Review

Khushboo Munir, Hassan Elahi, Afsheen Ayub, Fabrizio Frezza, Antonello Rizzi
2019 Cancers  
The purpose of this bibliographic review is to provide researchers opting to work in implementing deep learning and artificial neural networks for cancer diagnosis a knowledge from scratch of the state-of-the-art  ...  Considering the length of the manuscript, we restrict ourselves to the discussion of breast cancer, lung cancer, brain cancer, and skin cancer.  ...  Recurrent Neural Networks (RNNs) Recurrent neural networks are a powerful model of sequential data [126] .  ... 
doi:10.3390/cancers11091235 pmid:31450799 pmcid:PMC6770116 fatcat:ktuuttdu6zc7phj3mahp5yynxq

Cancer Detection by Machine Learning

Md Haris Uddin Sharif
2021 Zenodo  
Abstract— Cancer is a terminal condition, often caused by the aggregation of genetic defects and several disease modifications.  ...  In conclusion, obstacles for potential future work are also outlined. Index Terms—Artificial Intelligence, Biomedical Image Analysis, Cancer diagnosis, Deep neural network, Machine Learning.  ...  A sample of the Lungs Image Consortium is used for the assessment (LIDC) [09]. III.  ... 
doi:10.5281/zenodo.4578330 fatcat:fd6wv6rgujewzpmyxngczpeoca

Machine auscultation: enabling machine diagnostics using convolutional neural networks and large-scale machine audio data

Ruo-Yu Yang, Rahul Rai
2019 Advances in Manufacturing  
Microphones are used to collect acoustic data for training models from a computer numeric control (CNC) lathe. Numerical experiments demonstrate that CNN performs better than the BP-NN.  ...  This paper outlines two neural network models to analyze and classify acoustic signals emanating from machines: (i) a backpropagation neural network (BP-NN); and (ii) a convolutional neural network (CNN  ...  Introduction Auscultation is the act of listening to the internal sounds of organs such as the heart and lungs for diagnosing pathological disorders.  ... 
doi:10.1007/s40436-019-00254-5 fatcat:nitk52hzcnchlfosx4smzgwduq

On Interpretability of Artificial Neural Networks: A Survey [article]

Fenglei Fan, Jinjun Xiong, Mengzhou Li, Ge Wang
2021 arXiv   pre-print
However, the black-box nature of DNNs has become one of the primary obstacles for their wide acceptance in mission-critical applications such as medical diagnosis and therapy.  ...  Due to the huge potential of deep learning, interpreting neural networks has recently attracted much research attention.  ...  The authors are grateful for Dr. Hongming Shan's suggestions (Fudan University) and anonymous reviewers' advice.  ... 
arXiv:2001.02522v4 fatcat:pxa66n2wfjcbxfwc3k5gm3r2xa

Bioacoustics Data Analysis – A Taxonomy, Survey and Open Challenges

Rama Rao Kvsn, James Montgomery, Saurabh Garg, Michael Charleston
2020 IEEE Access  
Biodiversity monitoring has become a critical task for governments and ecological research agencies for reducing significant loss of animal species.  ...  Bioacoustics based monitoring is becoming an increasingly prominent non-invasive method, involving the passive recording of animal sounds.  ...  These 12 features are used to train a singleton-type recurrent fuzzy neural network, which achieved a high recognition rate. Cai et al.  ... 
doi:10.1109/access.2020.2978547 fatcat:nk3dcbv2evbpdp6g4fbovccqla

A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network

Yan Yan, Xu-Jing Yao, Shui-Hua Wang, Yu-Dong Zhang
2021 Biology  
The advantages of a convolutional neural network in tumor diagnosis are increasingly obvious.  ...  It provides a reference for developing a CNN computer-aided system based on tumor detection research in the future.  ...  Acknowledgments: Thanks to Si-Yuan Lu for his contribution to the revision of the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/biology10111084 pmid:34827077 pmcid:PMC8615026 fatcat:dr3b5ozqx5eppdqoara4wctefq

A Review of Deep Learning Algorithms and Their Applications in Healthcare

Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah, Malak EL-Amir
2022 Algorithms  
Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain.  ...  For new researchers in the field of deep learning, this review can help them to obtain many details about the advantages, disadvantages, applications, and working mechanisms of a number of deep learning  ...  Acknowledgments: The authors would like to thank the Arab Open University for supporting this research paper. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/a15020071 fatcat:ku5mfuijdjfxxdv7hlkexad7dy

Modality specific U-Net variants for biomedical image segmentation: A survey [article]

Narinder Singh Punn, Sonali Agarwal
2022 arXiv   pre-print
In recent studies, U-Net based approaches have illustrated state-of-the-art performance in different applications for the development of computer-aided diagnosis systems for early diagnosis and treatment  ...  With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most widely utilized in biomedical  ...  Acknowledgment We thank our institute, Indian Institute of Information Technology Allahabad (IIITA), India and Big Data Analytics (BDA) lab for allocating the necessary  ... 
arXiv:2107.04537v4 fatcat:m5oqea5q6vhbhkerjmejder3hu

Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic

Nora El-Rashidy, Samir Abdelrazik, Tamer Abuhmed, Eslam Amer, Farman Ali, Jong-Wan Hu, Shaker El-Sappagh
2021 Diagnostics  
Five significant applications of AI for COVID-19 were found, including (1) COVID-19 diagnosis using various data types (e.g., images, sound, and text); (2) estimation of the possible future spread of the  ...  The main objective of this study is to survey the decisive role of AI as a technology used to fight against the COVID-19 pandemic.  ...  They composited a hyper feature extraction technique of the main four filters, namely, a Gabor filter, MPEG-7 histogram filter, fuzzy-64, and local binary histogram.  ... 
doi:10.3390/diagnostics11071155 pmid:34202587 pmcid:PMC8303306 fatcat:ne2tivgcbrfa7kvtrhaqzgkoba

A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19 [article]

Jianguo Chen, Kenli Li, Zhaolei Zhang, Keqin Li, Philip S. Yu
2021 arXiv   pre-print
This survey presents medical and AI researchers with a comprehensive view of the existing and potential applications of AI technology in combating COVID-19 with the goal of inspiring researchers to continue  ...  In addition, we summarize the available data and resources that can be used for AI-based COVID-19 research.  ...  The proposed system connects fuzzy logic and neural networks and uses and enhanced Flower Pollination Algorithm (FPA) [232] for model parameter optimization and model training.  ... 
arXiv:2007.02202v2 fatcat:ss6r2ijaq5d7hi6qlrpwcnltvi

2021 Index IEEE Transactions on Instrumentation and Measurement Vol. 70

2021 IEEE Transactions on Instrumentation and Measurement  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, and article number.  ...  ., +, TIM 2021 5009612 Kalman Filter-Based Convolutional Neural Network for Robust Tracking of Froth-Middling Interface in a Primary Separation Vessel in Presence of Occlusions.  ... 
doi:10.1109/tim.2022.3156705 fatcat:dmqderzenrcopoyipv3v4vh4ry

Deep Learning Meets Hyperspectral Image Analysis: A Multidisciplinary Review

Alberto Signoroni, Mattia Savardi, Annalisa Baronio, Sergio Benini
2019 Journal of Imaging  
Deep learning approaches certainly offer a great variety of opportunities for solving classical imaging tasks and also for approaching new stimulating problems in the spatial–spectral domain.  ...  Modern hyperspectral imaging systems produce huge datasets potentially conveying a great abundance of information; such a resource, however, poses many challenges in the analysis and interpretation of  ...  Recurrent Neural Networks Recurrent neural networks (RNNs) belong to an important branch of the DL family and are mainly designed to handle sequential data (see Figure A1c) .  ... 
doi:10.3390/jimaging5050052 pmid:34460490 fatcat:ledlmt42bfdtdhe7tvj2dl2rwm

Different Data Mining Approaches Based Medical Text Data

Wenke Xiao, Lijia Jing, Yaxin Xu, Shichao Zheng, Yanxiong Gan, Chuanbiao Wen, Óscar Belmonte Fernández
2021 Journal of Healthcare Engineering  
The amount of medical text data is increasing dramatically. Medical text data record the progress of medicine and imply a large amount of medical knowledge.  ...  We also explored the applications of algorithms for providing insights to the users and enabling them to use the resources for the specific challenges in medical text data.  ...  NLP pipeline.  ... 
doi:10.1155/2021/1285167 pmid:34912530 pmcid:PMC8668297 fatcat:sr6zc5lfpvabdfgcd57uif76m4

Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19

Hanan Farhat, George E. Sakr, Rima Kilany
2020 Machine Vision and Applications  
Yet, coronavirus can be the real trigger to open the route for fast integration of DL in hospitals and medical centers.  ...  It summarizes and discusses the current state-of-the-art approaches in this research domain, highlighting the challenges, especially with COVID-19 pandemic current situation.  ...  [217] covered the entire pipeline of AI medical imaging analysis techniques for COVID-19.  ... 
doi:10.1007/s00138-020-01101-5 pmid:32834523 pmcid:PMC7386599 fatcat:tkkylrptc5hkpoj52hjs3kuttu
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