Artificial intelligence for caries and periapical periodontitis detection

Journal of Dentistry, Год журнала: 2022, Номер 122, С. 104107 - 104107

Опубликована: Март 25, 2022

Язык: Английский

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Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment

Healthcare, Год журнала: 2023, Номер 11(5), С. 683 - 683

Опубликована: Фев. 25, 2023

This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting limitations. The aim was evaluate accuracy and efficiency current AI-based systems compared conventional methods diagnosing, assessing progress patients’ treatment follow-up stability. researchers used various online databases identified diagnostic dental monitoring as most studied orthodontics. former can accurately identify anatomical landmarks for cephalometric analysis, while latter enables orthodontists thoroughly monitor each patient, determine specific desired outcomes, track progress, warn changes pre-existing pathology. However, there is limited evidence assess stability outcomes relapse detection. study concludes that AI an effective tool managing orthodontic from diagnosis retention, benefiting both patients clinicians. Patients find easy use feel better cared for, clinicians make diagnoses more easily compliance damage braces or aligners quickly frequently.

Язык: Английский

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The Use and Performance of Artificial Intelligence in Prosthodontics: A Systematic Review

Sensors, Год журнала: 2021, Номер 21(19), С. 6628 - 6628

Опубликована: Окт. 5, 2021

(1) Background: The rapid pace of digital development in everyday life is also reflected dentistry, including the emergence first systems based on artificial intelligence (AI). This systematic review focused recent scientific literature and provides an overview application AI dental discipline prosthodontics. (2) Method: According to a modified PICO-strategy, electronic (MEDLINE, EMBASE, CENTRAL) manual search up 30 June 2021 was carried out for published last five years reporting use field (3) Results: 560 titles were screened, which abstracts 16 full texts selected further review. Seven studies met inclusion criteria analyzed. Most identified reported training system (n = 6) or explored function intrinsic CAD software 1). (4) Conclusions: While number included relatively low, summary obtained findings by represents latest developments prosthodontics demonstrating its automated diagnostics, as predictive measure, classification identification tool. In future, technologies will likely be used collecting, processing, organizing patient-related datasets provide patient-centered, individualized treatment.

Язык: Английский

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Deep Machine Learning for Oral Cancer: From Precise Diagnosis to Precision Medicine

Frontiers in Oral Health, Год журнала: 2022, Номер 2

Опубликована: Янв. 11, 2022

Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide and its incidence on rise in many populations. The high rate, late diagnosis, improper treatment planning still form a significant concern. Diagnosis at an early-stage important for better prognosis, treatment, survival. Despite recent improvement understanding molecular mechanisms, diagnosis approach toward precision medicine OSCC patients remain challenge. To enhance medicine, deep machine learning technique has been touted to early detection, consequently reduce cancer-specific mortality morbidity. This reported have made progress data extraction analysis vital information medical imaging years. Therefore, it potential assist detection oral carcinoma. Furthermore, automated image can pathologists clinicians make informed decision regarding cancer patients. article discusses technical knowledge algorithms OSCC. It examines application technology classification, segmentation synthesis, planning. Finally, we discuss how this future perspective

Язык: Английский

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Contemporary Role and Applications of Artificial Intelligence in Dentistry

F1000Research, Год журнала: 2023, Номер 12, С. 1179 - 1179

Опубликована: Сен. 20, 2023

Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, smart cities. AI has the potential to improve quality of patient care treatment outcomes while minimizing risk human error. Artificial is transforming dental industry, just like it revolutionizing other sectors. It used in dentistry diagnose diseases provide recommendations. Dental professionals are increasingly relying on technology assist diagnosis, clinical decision-making, planning, prognosis prediction across ten specialties. One most advantages its ability analyze vast amounts data quickly accurately, providing with valuable insights enhance their decision-making processes. The purpose this paper identify advancement artificial intelligence algorithms that have been frequently assess how well they perform terms treatment, specialties; public health, endodontics, oral maxillofacial surgery, medicine pathology, & radiology, orthodontics dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, digital general. We will also show pros cons using all specialties different ways. Finally, we present limitations which made incapable replacing personnel, dentists, who should consider complimentary benefit not threat.

Язык: Английский

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Biological biomarkers of oral cancer

Periodontology 2000, Год журнала: 2023, Номер 96(1), С. 250 - 280

Опубликована: Дек. 10, 2023

The oral squamous cell carcinoma (OSCC) 5 year survival rate of 41% has marginally improved in the last few years, with less than a 1% improvement per from 2005 to 2017, higher rates when detected at early stages. Based on histopathological grading dysplasia, it is estimated that severe dysplasia malignant transformation 7%-50%. Despite these numbers, does not reliably predict its clinical behavior. Thus, more accurate markers predicting progression cancer would enable better targeting lesions for closer follow-up, especially stages disease. In this context, molecular biomarkers derived genetics, proteins, and metabolites play key roles oncology. These signatures can help likelihood OSCC development and/or have potential detect disease an stage and, support treatment decision-making responsiveness. Also, identifying reliable detection be obtained non-invasively enhance management OSCC. This review will discuss emerged different biological areas, including genomics, transcriptomics, proteomics, metabolomics, immunomics, microbiomics.

Язык: Английский

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AI and Face-Driven Orthodontics: A Scoping Review of Digital Advances in Diagnosis and Treatment Planning

AI, Год журнала: 2024, Номер 5(1), С. 158 - 176

Опубликована: Янв. 5, 2024

In the age of artificial intelligence (AI), technological progress is changing established workflows and enabling some basic routines to be updated. dentistry, patient’s face a crucial part treatment planning, although it has always been difficult grasp in an analytical way. This review highlights current digital advances that, thanks AI tools, allow us implement facial features beyond symmetry proportionality incorporate analysis into diagnosis planning orthodontics. A Scopus literature search was conducted identify topics with greatest research potential within orthodontics over last five years. The most researched cited topic its applications Apart from automated 2D or 3D cephalometric analysis, finds application decision-making algorithms as well evaluation retention. Together AI, other are shaping today’s Without any doubts, era “old” at end, modern, face-driven on way becoming reality modern orthodontic practices.

Язык: Английский

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Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms

Oral Radiology, Год журнала: 2024, Номер 40(3), С. 375 - 384

Опубликована: Март 18, 2024

Язык: Английский

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Artificial Intelligence for Osteoporosis Detection on Panoramic Radiography: A Systematic Review and Meta Analysis

Journal of Dentistry, Год журнала: 2025, Номер unknown, С. 105650 - 105650

Опубликована: Фев. 1, 2025

Язык: Английский

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Histopathology-Based Diagnosis of Oral Squamous Cell Carcinoma Using Deep Learning

Journal of Dental Research, Год журнала: 2022, Номер 101(11), С. 1321 - 1327

Опубликована: Апрель 21, 2022

Oral squamous cell carcinoma (OSCC) is prevalent around the world and associated with poor prognosis. OSCC typically diagnosed from tissue biopsy sections by pathologists who rely on their empirical experience. Deep learning models may improve accuracy speed of image classification, thus reducing human error workload. Here we developed a custom-made deep model to assist in detecting histopathology images. We collected analyzed total 2,025 images, among which 1,925 images were included training set 100 testing set. Our was able automatically evaluate these arrive at diagnosis sensitivity 0.98, specificity 0.92, positive predictive value 0.924, negative 0.978, F1 score 0.951. Using subset examined whether our could diagnostic performance junior senior pathologists. found that delineate 6.26 min faster when assisted than working alone. When clinicians model, average improved 0.9221 0.9566 case 0.9361 0.9463 findings indicate can

Язык: Английский

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