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A Review of Different Methods for Automatic Diagnosis of Oral Cancer
2020
International journal of recent technology and engineering
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Optical Coherence Tomography and a variety of Machine Learning based techniques, including Artificial Neural Networks (ANNs), Bayesian Networks (BNs), Tree Boost Model are discussed in this paper. ...
Oral cancer is having 6th rank out of all cancers in the world. There might be tumor in salivary glands, tonsils and also in neck, head, face and oral cavity. ...
In this system early diagnosis of oral cancer is done with the help of 3 Dimensional Convolution Network. It early diagnose malignant and benign. A. E. Heidari, S. P. Sunny, B. L. James, T. M. ...
doi:10.35940/ijrte.b4177.079220
fatcat:erezgrmpefenzflyb4ttodri4e
Machine learning in dental, oral and craniofacial imaging: a review of recent progress
2021
PeerJ
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The popularity of convolutional neural network in dental, oral and craniofacial imaging is heightening, as it has been continually applied to a broader spectrum of scientific studies. ...
One major application of artificial intelligence in medical science is medical imaging. ...
For example, the application of three-dimensional convolution to medical imaging can compensate for the three-dimensional features of organ tissues that cannot be extracted by traditional two-dimensional ...
doi:10.7717/peerj.11451
pmid:34046262
pmcid:PMC8136280
fatcat:y46lhvahffah7h7ru7hmmsskve
Clinical applications and performance of intelligent systems in dental and maxillofacial radiology: A review
2020
Imaging Science in Dentistry
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of oral cancer risk, and the assessment of metastatic lymph nodes, periapical pathologies, and maxillary sinus pathologies. ...
Intelligent systems have an important role to play and could be used by dentists as an adjunct to other imaging modalities in making appropriate diagnoses and treatment plans. ...
Recently, Ariji et al. 9 found that the use of a convolutional neural network enhanced the CT-based diagnosis of lymph node metastasis. ...
doi:10.5624/isd.2020.50.2.81
pmid:32601582
pmcid:PMC7314602
fatcat:5bai4q4qvzhpdj4krxc4sdbgmy
Spatio-spectral deep learning methods for in-vivo hyperspectral laryngeal cancer detection
[article]
2020
arXiv
pre-print
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For this purpose we design and evaluate convolutional neural networks (CNNs) with 2D spatial or 3D spatio-spectral convolutions combined with a state-of-the-art Densenet architecture. ...
For evaluation, we use an in-vivo data set with HSI of the oral cavity or oropharynx. ...
applications ranging from agriculture, food quality to biomedicine. 12 In particular, previous studies evaluated convolutional neural networks (CNNs) for classifying head and neck cancer based on HSI ...
arXiv:2004.10159v1
fatcat:musv7dpwmbbbxamkup26fwls5i
Chalk and Talk Versus Powerpoint: Perception among Medical Students
2021
Medico-Legal Update
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The main advantage of the deep learning algorithm is that it requires minimum number of oral images for both classification and diagnosis stages of the proposed work. ...
In this paper, the total number of cancers affected oral images used is about 160 and the proposed oral cancer detection system using CNN classification approach classifies 159 cancer affected oral images ...
Figure 1 shows the proposed oral cancer classification and diagnosis system using Convolutional Neural Network (CNN) classification approach. ...
doi:10.37506/mlu.v21i1.2353
fatcat:6s7oy6gyljhz3jroyejoxt2ccu
Artificial Intelligence in Diagnosis of Oral Potentially Malignant Lesions- Need of the Hour
2021
Journal of Pharmaceutical Research International
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Although artificial intelligence (AI) is beginning to have a significant impact on increasing diagnosis accuracy in a variety of fields of medicine, there has been limited research on oral cancer to date ...
The concepts of image-based techniques for identifying oral cancer are defined in terms of clinical requirements and features. ...
Postprocessing Convolutional neural networks (CNNs), recurrent neural networks (RNNs), multiscale convolutional neural networks (M-CNN), and multi-instance learning convolution neural networks are among ...
doi:10.9734/jpri/2021/v33i58a34092
fatcat:zevo5ypepjg33nqelmmsede6xm
Oral Cancer Screening by Artificial Intelligence-Oriented Interpretation of Optical Coherence Tomography Images
2022
Radiology Research and Practice
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Early diagnosis of oral cancer is critical to improve the survival rate of patients. ...
This literature review aimed to highlight the features of precancerous and cancerous oral lesions on OCT images and specify how AI can assist in screening and diagnosis of such pathologies. ...
((artificial intelligence) OR (machine learning) OR (deep learning) OR (convolutional neural network)). e inclusion criteria included studies that investigated oral precancerous or cancerous lesions on ...
doi:10.1155/2022/1614838
pmid:35502299
pmcid:PMC9056242
fatcat:d3myqr2t55c2jonto2ttawllsa
Application and Performance of Artificial Intelligence Technology in Oral Cancer Diagnosis and Prediction of Prognosis: A Systematic Review
2021
Diagnostics
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Oral cancer (OC) is a deadly disease with a high mortality and complex etiology. Artificial intelligence (AI) is one of the outstanding innovations in technology used in dental science. ...
This paper intends to report on the application and performance of AI in diagnosis and predicting the occurrence of OC. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/diagnostics11061004
pmid:34072804
fatcat:jt3skrnzlrd2relkkyqlssb7be
Analysis and Classification of H&E-Stained Oral Cavity Tumour Gradings Using Convolution Neural Network
2021
International Journal of Intelligent Engineering and Systems
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Upper Aero Digestive Tract (UADT) cancer is one of the most common cancer types in any gender. Early detection and diagnosing such type of cancer will reduce the risk of death in human. ...
The proposed CNN model is developed to classify different oral cavity tumour sites and its gradings automatically. ...
Acknowledgments The authors would like to acknowledge Ministry of Electronics and Information Technology (MeitY's), Government of India for funding the research work under Visvesvaraya PhD scheme. ...
doi:10.22266/ijies2021.1031.45
fatcat:36schsapmvd3bcpbwfni5o2s24
A Review on Recent Advancements in Diagnosis and Classification of Cancers Using Artificial Intelligence
2020
BioMedicine
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This article reviews the strategies and algorithms developed using artificial intelligence for the foremost cancer diagnosis and classification which overcomes the challenges in the traditional method. ...
However, with significant advancements in artificial intelligence strategy, the diagnostic and classifying capabilities of CAD system are meeting the levels of radiologists and clinicians. ...
Acknowledgements The authors grately acknowledge Vellore Institute of Technology for providing the facilities and support to carry out this work. ...
doi:10.37796/2211-8039.1012
pmid:33854922
pmcid:PMC7721470
fatcat:t3wt6f5cdfdfrfa26fieqjjnb4
Front Matter: Volume 10572
2017
13th International Conference on Medical Information Processing and Analysis
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
. The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03, ...
nodules with three-dimensional convolutional neural
networks [10572-48]
10572 19
Characterization of physiological networks in sleep apnea patients using artificial neural
networks for Granger causality ...
doi:10.1117/12.2310208
dblp:conf/sipaim/X17
fatcat:5mpaoft6nfcwrbrauhmpsgzemy
Learning Techniques for Pre-Malignancy Detection in Human Cells a Review
2020
International Journal of Engineering and Advanced Technology
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Early-stage detection of cancer helps in better diagnosis will also lower the chances of dying due to this deadly disease. ...
Cancer is uncontrolled cell growth which starts consuming cell nourishment and keeps on multiplying indefinably. There are 100 plus different types of cancers that may affect any part of the body. ...
Oral Cancer is among the top three cancers in India, number one among all cancers in men, and number three among female cancers. Breast cancer is first in females and then cervical [10, 11, 12] . ...
doi:10.35940/ijeat.f1622.089620
fatcat:t6n4f5d4kreybnofyavy5dzmp4
Analysis of Curative Effect and Prognostic Factors of Radiotherapy for Esophageal Cancer Based on the CNN
2021
Journal of Healthcare Engineering
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In this paper, by collecting medical images related to esophageal cancer over the years, we establish an intelligent diagnosis system based on the convolutional neural network for esophageal cancer images ...
The convolutional neural network-based esophageal cancer image intelligent diagnosis system has been successfully applied in hospitals and widely praised by frontline doctors. ...
cancer with convolutional neural network technology. rough learning and analysis of tens of thousands of esophageal endoscopy data, an early esophageal cancer intelligent diagnosis tool is created to ...
doi:10.1155/2021/9350677
pmid:34868534
pmcid:PMC8639232
fatcat:4otjrwcp6fckbbeowsgrghdkxi
Deep Learning in Head and Neck Tumor Multiomics Diagnosis and Analysis: Review of the Literature
2021
Frontiers in Genetics
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Among the DL techniques, the convolution neural network (CNN) is used for image segmentation, detection, and classification and in computer-aided diagnosis. ...
Here, we reviewed multiomics image analysis of head and neck tumors using CNN and other DL neural networks. ...
Similarly, confocal laser endomicroscopy (CLE) allows real-time visualization of epithelium in vivo and enables early diagnosis of oral cancer and prediction of the prognosis. ...
doi:10.3389/fgene.2021.624820
pmid:33643386
pmcid:PMC7902873
fatcat:eofflp46c5h6pd5gbni7sdnp5u
A deep learning algorithm for detection of oral cavity squamous cell carcinoma from photographic images: A retrospective study
2020
EClinicalMedicine
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We developed an automated deep learning algorithm using cascaded convolutional neural networks to detect OCSCC from photographic images. ...
We also compared the performance of the algorithm with that of seven oral cancer specialists on a clinical validation dataset. ...
On the resulting plots of t-SNE representations of these three lesion classes, [22] each point represents one oral photo projected from the 1024-dimensional output of the last hidden layer of our neural ...
doi:10.1016/j.eclinm.2020.100558
pmid:33150326
pmcid:PMC7599313
fatcat:4cltrh7enrfujaarjpa6fs6vzu
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