The current landscape of artificial intelligence in oral and maxillofacial surgery– a narrative review

Oral and Maxillofacial Surgery, Journal Year: 2025, Volume and Issue: 29(1)

Published: Jan. 17, 2025

Language: Английский

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A Refined Approach to Segmenting and Quantifying Inter-Fracture Spaces in Facial Bone CT Imaging

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(3), P. 1539 - 1539

Published: Feb. 3, 2025

The human facial bone is made up of many complex structures, which makes it challenging to accurately analyze fractures. To address this, we developed advanced image analysis software segments and quantifies spaces between fractured bones in CT images at the pixel level. This study used 3D scans from 1766 patients who had fractures a university hospital 2014 2020. Our solution included segmentation model focuses on identifying gaps created by However, training this required costly pixel-level annotations. overcome stepwise annotation approach. First, clinical specialists marked bounding boxes fracture areas. Next, trained initial unrefined ground truth referencing boxes. Finally, refined correct errors, helped improve accuracy. Radiomics feature confirmed that dataset more consistent patterns compared with dataset, showing improved reliability. showed significant improvement Dice similarity coefficient, increasing 0.33 0.67 truth. research introduced new method for segmenting bones, allowing precise identification regions. also quantitative severity assessment enabled creation volume renderings, can be settings develop accurate treatment plans outcomes

Language: Английский

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Role of artificial intelligence in clinical practice

IP Annals of Prosthodontics and Restorative Dentistry, Journal Year: 2025, Volume and Issue: 11(1), P. 4 - 9

Published: Feb. 15, 2025

Artificial Intelligence (AI) has revolutionized numerous fields, including dentistry, offering transformative potential in diagnosis, treatment planning, and patient care. With its ability to replicate human intelligence process complex data sets, AI provides innovative solutions across various dental specialties. This review discusses AI's role clinical emphasizing applications, benefits, limitations, future prospects fields like radiology, orthodontics, periodontics, prosthodontics, endodontics. Currently, the application of convoluted neural network (CNN)s is more common field. Moreover, it offers a glimpse into applications on integration with virtual reality, augmented reality metaverse.

Language: Английский

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Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach

Deleted Journal, Journal Year: 2024, Volume and Issue: unknown

Published: July 1, 2024

Abstract This study aims to evaluate an AI model designed automatically classify skull fractures and visualize segmentation on emergent CT scans. The model’s goal is boost diagnostic accuracy, alleviate radiologists’ workload, hasten diagnosis, thereby enhancing patient outcomes. Unique this research, both pediatric post-operative patients were not excluded, durations analyzed. Our testing dataset for the observer studies involved 671 patients, with a mean age of 58.88 years fairly balanced gender representation. Model 1 our algorithm, trained 1499 fracture-positive cases, showed sensitivity 0.94 specificity 0.87, DICE score 0.65. Implementing post-processing rules (specifically Rule B) improved performance, resulting in 0.94, 0.99, 0.63. AI-assisted diagnosis resulted significantly enhanced performance all participants, almost doubling junior radiology residents other specialists. Additionally, reduced ( p < 0.01) assistance across participant categories. fracture detection model, employing approach, demonstrated high accuracy efficiency radiologists clinical physicians. underlines potential integration medical imaging analysis improve care.

Language: Английский

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Very fast, high-resolution aggregation 3D detection CAM to quickly and accurately find facial fracture areas

Computer Methods and Programs in Biomedicine, Journal Year: 2024, Volume and Issue: 256, P. 108379 - 108379

Published: Aug. 19, 2024

The incidence of facial fractures is on the rise globally, yet limited studies are addressing diverse forms present in 3D images. In particular, due to nature fracture, direction which bone vary, and there no clear outline, it difficult determine exact location fracture 2D Thus, image analysis required find area, but needs heavy computational complexity expensive pixel-wise labeling for supervised learning. this study, we tackle problem reducing burden increasing accuracy localization by using a weakly-supervised object without space.

Language: Английский

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Addressing the Challenges in Pediatric Facial Fractures: A Narrative Review of Innovations in Diagnosis and Treatment

Surgeries, Journal Year: 2024, Volume and Issue: 5(4), P. 1130 - 1146

Published: Dec. 13, 2024

Background/Objectives: Pediatric facial fractures present unique challenges due to the anatomical, physiological, and developmental differences in children’s structures. The growing bones children complicate diagnosis treatment. This review explores advancements complexities managing pediatric fractures, focusing on innovations diagnosis, treatment strategies, multidisciplinary care. Methods: A narrative was conducted, synthesizing data from English-language articles published between 2001 2024. Relevant studies were identified through databases such as PubMed, Scopus, Lilacs, Embase, SciELO using keywords related fractures. focuses anatomical challenges, diagnostic techniques, approaches, role of interdisciplinary teams management. Results: Key findings highlight imaging technologies, including three-dimensional computed tomography (3D CT) magnetic resonance (MRI), which have improved fracture preoperative planning. Minimally invasive techniques bioresorbable implants revolutionized treatment, reducing trauma enhancing recovery. integration teams, pediatricians, psychologists, speech therapists, has become crucial addressing both physical emotional needs patients. Emerging technologies 3D printing computer-assisted navigation are shaping future approaches. Conclusions: management significantly advanced imaging, surgical importance Despite these improvements, long-term follow-up remains critical monitor potential complications. Ongoing research collaboration essential refine strategies improve outcomes for patients with trauma.

Language: Английский

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Artificial Intelligence in Oral and Maxillofacial Surgery: Bridging the Gap between Technology and Clinical Practice a Narrative Review

International Journal of Innovative Science and Research Technology (IJISRT), Journal Year: 2024, Volume and Issue: unknown, P. 114 - 119

Published: Oct. 15, 2024

Objective: To provide a comprehensive overview of current applications and future prospects artificial intelligence (AI) in oral maxillofacial surgery (OMFS), while critically analyzing implementation challenges exploring potential advancements.  Methods A systematic literature review was conducted using PubMed/MEDLINE Embase databases, encompassing English-language articles up to December 30, 2023. Search terms combined OMFS AI concepts, with database-specific syntax employed. Results span multiple domains, including image analysis, surgical planning, intraoperative guidance, clinical decision support. Deep learning models have demonstrated high accuracy detecting mandibular fractures, performing cephalometric analyses, classifying pathologies. AI-enhanced planning robotic systems show promise improving precision outcomes across various procedures. However, persist data quality, validation, seamless workflow integration. Conclusions technologies the significantly enhance diagnostic accuracy, precision, treatment OMFS. Future research directions include developing multimodal systems, advancing AI-powered navigation, federated approaches. Successful practice will require collaborative efforts among clinicians, researchers, engineers, policymakers address technical, ethical, regulatory challenges. As these hurdles are overcome, is poised become an integral part OMFS, augmenting capabilities elevating patient care standards.

Language: Английский

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Machine Learning for Treatment Management Prediction in Laryngeal Fractures

Journal of Voice, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Language: Английский

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Clinical deployment of machine learning models in craniofacial surgery: considerations for adoption and implementation

Artificial Intelligence Surgery, Journal Year: 2024, Volume and Issue: 4(4), P. 427 - 34

Published: Dec. 13, 2024

The volume and complexity of clinical data are growing rapidly. potential for artificial intelligence (AI) machine learning (ML) to significantly impact plastic craniofacial surgery is immense. This manuscript reviews the overall landscape AI in surgery, highlighting scarcity prospective clinically translated models. It examines numerous promises challenges associated with AI, such as lack robust legislation structured frameworks its integration into medicine. Clinical translation considerations discussed, including importance ensuring utility real-world use. Finally, this commentary brings forward how clinicians can build trust sustainability toward model-driven care.

Language: Английский

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