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A Review of Different Methods for Automatic Diagnosis of Oral Cancer

2020 International journal of recent technology and engineering  
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

Ruiyang Ren, Haozhe Luo, Chongying Su, Yang Yao, Wen Liao
2021 PeerJ  
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

Ravleen Nagi, Konidena Aravinda, N Rakesh, Rajesh Gupta, Ajay Pal, Amrit Kaur Mann
2020 Imaging Science in Dentistry  
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]

Marcel Bengs and Stephan Westermann and Nils Gessert and Dennis Eggert and Andreas O. H. Gerstner and Nina A. Mueller and Christian Betz and Wiebke Laffers and Alexander Schlaefer
2020 arXiv   pre-print
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  
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

Abhilasha Chapade, Kumar Gaurav Chhabra, Amit Reche, Priyanka Paul Madhu
2021 Journal of Pharmaceutical Research International  
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

Kousar Ramezani, Maryam Tofangchiha, André Luiz Ferreira Costa
2022 Radiology Research and Practice  
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

Sanjeev B. Khanagar, Sachin Naik, Abdulaziz Abdullah Al Kheraif, Satish Vishwanathaiah, Prabhadevi C. Maganur, Yaser Alhazmi, Shazia Mushtaq, Sachin C. Sarode, Gargi S. Sarode, Alessio Zanza, Luca Testarelli, Shankargouda Patil
2021 Diagnostics  
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

Prabhakaran Mathialagan, SRM Institute of Science and Technology
2021 International Journal of Intelligent Engineering and Systems  
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

Priyanka Ramesh, Ramanathan Karuppasamy, Shanthi Veerappapillai
2020 BioMedicine  
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

Jorge Brieva, Juan David García, Natasha Lepore, Eduardo Romero
2017 13th International Conference on Medical Information Processing and Analysis  
Publication of record for individual papers is online in the SPIE Digital Library. 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  
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

Yunhui Zhao, Junkai Xu, Qisong Chen, Rahim Khan
2021 Journal of Healthcare Engineering  
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

Xi Wang, Bin-bin Li
2021 Frontiers in Genetics  
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

Qiuyun Fu, Yehansen Chen, Zhihang Li, Qianyan Jing, Chuanyu Hu, Han Liu, Jiahao Bao, Yuming Hong, Ting Shi, Kaixiong Li, Haixiao Zou, Yong Song (+16 others)
2020 EClinicalMedicine  
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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