Artificial intelligence in early diagnosis and prevention of oral cancer

Hegde, Shruthi; Ajila, Vidya; Zhu, Wenwu; Zeng, Canhui

doi:10.1016/j.apjon.2022.100133

Cited by 28 publications

(15 citation statements)

References 51 publications

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“…Predictive analytics: AI can help predict the likelihood of certain dental problems and diseases based on a patient's data, helping to prevent and treat them ( 142 – 146 ).…”

Section: Advantages and Disadvantages Of Artificial Intelligence In D...mentioning

confidence: 99%

Artificial Intelligence in Medicine and Dentistry

Vodanović¹,

Subašić²,

Milošević³

et al. 2023

Acta Stomatol Croat

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Introduction Artificial intelligence has been applied in various fields throughout history, but its integration into daily life is more recent. The first applications of AI were primarily in academia and government research institutions, but as technology has advanced, AI has also been applied in industry, commerce, medicine and dentistry. Objective Considering that the possibilities of applying artificial intelligence are developing rapidly and that this field is one of the areas with the greatest increase in the number of newly published articles, the aim of this paper was to provide an overview of the literature and to give an insight into the possibilities of applying artificial intelligence in medicine and dentistry. In addition, the aim was to discuss its advantages and disadvantages. Conclusion The possibilities of applying artificial intelligence to medicine and dentistry are just being discovered. Artificial intelligence will greatly contribute to developments in medicine and dentistry, as it is a tool that enables development and progress, especially in terms of personalized healthcare that will lead to much better treatment outcomes.

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“…Predictive analytics: AI can help predict the likelihood of certain dental problems and diseases based on a patient's data, helping to prevent and treat them ( 142 – 146 ).…”

Section: Advantages and Disadvantages Of Artificial Intelligence In D...mentioning

confidence: 99%

Artificial Intelligence in Medicine and Dentistry

Vodanović¹,

Subašić²,

Milošević³

et al. 2023

Acta Stomatol Croat

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“…[12] To utilize artificial intelligence for disease diagnosis, artificial intelligence first needs to be able to perceive the surrounding environment like humans, particularly the status of the body, such as what a normal versus abnormal body entails, the presence of cancer in the body, or even minor changes in the body (i.e., a few cancerous cells in a very small biological environment). [11][12][13] This study enrolled 165 patients with periarthritis of the shoulder, who were admitted to our hospital from January 2020 to January 2022, to explore the value of artificial intelligence combined with musculoskeletal ultrasound in the differential diagnosis of pain rehabilitation of periarthritis of the shoulder.…”

Section: This Study Was Supported By the Key Scientific Project Of Wu...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of the value of artificial intelligence combined with musculoskeletal ultrasound in the differential diagnosis of pain rehabilitation of scapulohumeral periarthritis

Wang

et al. 2023

Medicine

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To explore the value of artificial intelligence combined with musculoskeletal ultrasound in the differential diagnosis of pain rehabilitation of scapulohumeral periarthritis. A total of 165 patients with periarthritis of the shoulder, who were admitted to our hospital from January 2020 to January 2022, were selected. Konica SONIMAGE HS1 PLUS color Doppler ultrasound diagnostic instrument was used to detect muscles and bones of patients with scapulohumeral periarthritis. This study proposed an intelligent clustering analysis algorithm with musculoskeletal ultrasound parameters. The neural network was trained on a GeForce RTX 3060 with the Adam W optimizer, a batch size of 12, and an initial learning rate of 5E-4. Each batch of 2 types of trained samples was input into the network in a specific proportion. Pain was assessed on a 10-point visual analogue scale. On the affected side of scapulohumeral periarthritis, the mild pain group showed thickening of the shoulder posterior capsule (2.02 ± 0.72) mm with clear edges. In the moderate pain group, the thickness of the shoulder posterior capsule gradually narrowed (1.01 ± 0.38) mm and became even thinner than that of the unaffected side, with irregular and blurred edges. In the severe pain group, the thickness of the shoulder posterior capsule largely returned to normal (1.21 ± 0.42) mm, and the edge was clear. Multivariate logistic regression showed that in addition to musculoskeletal ultrasound parameters, the length of service, work nature, and the busy degree of work of patients with periarthritis of the shoulder were significant factors that influenced shoulder periarthritis pain ( P < .05). The performance of the proposed intelligent auscultation algorithm was further examined in a clinical setting, in which we used 165 clinical musculoskeletal ultrasound samples (including 81 positive and 84 negative samples) as a test set. The accuracy, sensitivity, and specificity were 0.833, 0.872, and 0.801, respectively. Musculoskeletal ultrasound combined with artificial intelligence algorithm is a new diagnostic and staging tool for scapulohumeral periarthritis.

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“…Common applications of AI in oral diagnosis and dentomaxillofacial radiology are as follows: Oral cancer prognosis and assessment of oral cancer risk [ 45 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ]; Determination of temporomandibular joint disorder progression and temporomandibular internal derangements [ 27 , 30 , 34 , 38 , 63 ]; Interpretation of conventional 2D imaging [ 31 , 64 , 65 , 66 , 67 , 68 ]; Interpretation of cone beam computed tomography and other 3D imaging methods [ 1 , 10 , 12 , 17 , 18 , 19 , 21 , 23 , 27 , 69 , 70 , 71 ]. …”

Section: Introductionmentioning

confidence: 99%

“…Oral cancer prognosis and assessment of oral cancer risk [ 45 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ];…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of Teeth, Crown–Bridge Restorations, Dental Implants, Restorative Fillings, Dental Caries, Residual Roots, and Root Canal Fillings on Orthopantomographs: Convenience and Pitfalls

et al. 2023

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Background: The aim of our study is to provide successful automatic segmentation of various objects on orthopantomographs (OPGs). Methods: 8138 OPGs obtained from the archives of the Department of Dentomaxillofacial Radiology were included. OPGs were converted into PNGs and transferred to the segmentation tool’s database. All teeth, crown–bridge restorations, dental implants, composite–amalgam fillings, dental caries, residual roots, and root canal fillings were manually segmented by two experts with the manual drawing semantic segmentation technique. Results: The intra-class correlation coefficient (ICC) for both inter- and intra-observers for manual segmentation was excellent (ICC > 0.75). The intra-observer ICC was found to be 0.994, while the inter-observer reliability was 0.989. No significant difference was detected amongst observers (p = 0.947). The calculated DSC and accuracy values across all OPGs were 0.85 and 0.95 for the tooth segmentation, 0.88 and 0.99 for dental caries, 0.87 and 0.99 for dental restorations, 0.93 and 0.99 for crown–bridge restorations, 0.94 and 0.99 for dental implants, 0.78 and 0.99 for root canal fillings, and 0.78 and 0.99 for residual roots, respectively. Conclusions: Thanks to faster and automated diagnoses on 2D as well as 3D dental images, dentists will have higher diagnosis rates in a shorter time even without excluding cases.

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Artificial intelligence in early diagnosis and prevention of oral cancer

Cited by 28 publications

References 51 publications

Artificial Intelligence in Medicine and Dentistry

Artificial Intelligence in Medicine and Dentistry

Analysis of the value of artificial intelligence combined with musculoskeletal ultrasound in the differential diagnosis of pain rehabilitation of scapulohumeral periarthritis

Automatic Segmentation of Teeth, Crown–Bridge Restorations, Dental Implants, Restorative Fillings, Dental Caries, Residual Roots, and Root Canal Fillings on Orthopantomographs: Convenience and Pitfalls

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