Artificial intelligence in scientific peer review
Vinod Krishnan
Published in issue: April 2024
Artificial intelligence (AI) is transforming the scientific peer review process, offering innovative tools to streamline tasks like plagiarism detection, reviewer matching, and content analysis. As submission volumes grow, AI’s ability to assist in managing the workload has become invaluable, though its limitations remain clear. While AI can efficiently assess certain aspects of manuscripts, it struggles with recognizing novel research findings and maintaining the nuanced judgment required for high-quality peer review. A hybrid approach combining AI’s automation capabilities with human expertise is emerging as the optimal strategy to uphold the integrity and reliability of the peer review system.
Highlights:
- Enhanced Workflow Efficiency: AI assists with plagiarism detection, reviewer matching, and compliance checks.
- Potential Benefits: Tools like GPT-4 have been rated as providing helpful feedback by researchers, reducing reviewer workload.
- Ethical and Practical Limitations: AI cannot replace human reviewers due to challenges in evaluating innovation, methodology, and critical reasoning.
- Risks and Concerns: Ethical issues, algorithm bias, and the lack of transparency in AI models necessitate caution.
Hybrid Approach Advantage: Combining AI automation with human judgment ensures quality and integrity in the peer review process.
Aligner biomechanics: Where we are now and where we are heading for
Tommaso Castroflorio, Simone Parrini, Gabriele Rossini
Published online: January 15, 2024
The evolving field of aligner biomechanics is transforming orthodontic practices, offering a combination of aesthetics, comfort, and precision in tooth movement. By understanding the principles of aligner design, attachment placement, and material science, orthodontists can improve treatment predictability and expand the scope of cases treated with aligners. As clear aligners gain popularity, advances in technology and materials continue to refine their effectiveness, addressing complex malocclusions with innovative solutions.
Highlights:
- Attachments as Crucial Tools: Properly designed and placed attachments are essential for guiding tooth movements, such as rotation, extrusion, and bodily translation.
- Material Challenges: Aligner deformation remains a key obstacle; advancements in materials like shape memory polymers and bioactive resins show promise in improving outcomes.
- Expanded Scope of Treatment: Modern aligners now address complex cases, including Class II malocclusions and open bites, previously treated only with fixed appliances.
- Innovations in Technology: Developments in aligner fabrication, including 3D printing and customizable designs, enhance precision and reduce unwanted movements.
- Sustainability Focus: The ecological impact of aligners is gaining attention, with efforts toward sustainable materials and manufacturing practices.
Aligner orthodontics continues to redefine possibilities, blending biomechanics, aesthetics, and innovation for better patient outcomes.
Numerical biomechanical finite element analysis of different trimming line designs of orthodontic aligners: An in silico study
Tarek M. Elshazly, Christoph Bourauel, Philippe Chavanne, Hanaa Elattar, Ludger Keilig
Published online: February 23, 2024
Finite element analysis offers a detailed understanding of how the design and thickness of orthodontic aligners affect force distribution and tooth movement. This study evaluates various trimming line designs—scalloped, straight, and extended versions—and their biomechanical behavior, providing insights into optimizing aligner performance.
Highlights:
- Impact of Trimming Lines: Straight extended trimming lines enhance force distribution, improving torque control and tooth movement.
- Thickness Matters: Thicker aligners generate higher forces, but thinner aligners can offer greater comfort when paired with optimal trimming designs.
- Force Concentration: Extended trimming lines focus forces in the cervical third, closer to the tooth’s center of resistance, aiding controlled movement.
- Challenges in Tipping: All designs showed a tendency toward uncontrolled tipping rather than bodily movement, underscoring areas for further refinement.
- Clinical Relevance: Straight extended designs are recommended for better biomechanics, especially when using advanced materials like 3D-printed aligners.
This study underscores the importance of aligner design in orthodontic treatment, offering valuable guidance to practitioners and manufacturers in improving treatment outcomes and patient comfort.
Evaluation of pain intensity with prostaglandin E2 biomarker and visual analog scale during initiation of orthodontic treatment: A prospective study
Yuvashree Raghupathy, Venkateswaran Ananthanarayanan, Vignesh Kailasam
Published online: November 18, 2023 p72-77
Orthodontic treatments can be a painful experience for many, and understanding when and how pain peaks is essential for better patient care. This prospective study evaluated pain intensity during the initial stages of orthodontic treatment using both subjective (Visual Analog Scale, VAS) and objective (prostaglandin E2, PGE2 biomarker) assessments. It was found that pain intensity, measured with VAS, was highest between 24 and 48 hours after the initial archwire placement, coinciding with the peak PGE2 levels. However, the study revealed no significant correlation between PGE2 concentrations and VAS scores, suggesting that pain perception involves complex biological and psychological factors.
Highlights:
- Subjective and Objective Pain Assessment: Both VAS scores and PGE2 biomarker levels were used to evaluate pain intensity during orthodontic treatment.
- Pain Peaks at 48 Hours: The highest pain scores and PGE2 concentrations occurred between 24 and 48 hours post-treatment.
- Lack of Correlation: There was no significant statistical correlation between VAS pain scores and PGE2 levels, highlighting the complexity of pain perception.
- Clinical Implications: Analgesic use may be most beneficial between 24 and 72 hours to manage pain effectively.
Study Limitations: A longer assessment period and consideration of additional biomarkers could provide a more comprehensive understanding of pain mechanisms.
Comparisons of soft tissue changes after Herbst appliance treatment in three different growth phases
Juan Francisco Mariscal, Dirceu Barnabé Ravelli, Ary dos Santos Pinto, Gladys Cristina Dominguez, Luís Antônio de Arruda Aidar, Helder B. Jacob
Published online: December 27, 2023 p78-85
The Herbst appliance is commonly used to correct Class II malocclusion, but its effectiveness can vary based on the patient’s stage of craniofacial growth. This study compared the soft tissue changes produced by Herbst therapy in three growth phases: prepubertal (PRE), circumpubertal (CIR), and postpubertal (POS). Findings showed that soft tissue improvements, including facial convexity reduction and pogonion advancement, were more pronounced in the PRE and CIR phases. The research highlighted moderate correlations between skeletal and soft tissue changes, providing valuable insights for orthodontists in timing treatment for optimal outcomes.
Highlights:
- Growth Phase Impact: Herbst therapy’s soft tissue effects are more pronounced in the prepubertal and circumpubertal stages compared to the postpubertal stage.
- Facial Convexity: Greater reductions in facial convexity were observed in the PRE and CIR groups than in the POS group.
- Pogonion Advancement: The soft tissue pogonion showed the most advancement in the PRE group, with moderate correlation to skeletal changes.
- Mandibular Soft Tissue: Thickness increased notably at the B point and pogonion areas in the PRE group.
Correlation Insights: Skeletal and soft tissue facial convexity changes showed a moderate-low correlation, while skeletal and soft pogonion advancements had a moderate-high correlation.
Awareness about the orthodontic specialty: A survey study
Arslan Z., Elekdag-Türk S.
Published online: February 19, 2024 p86-94
Patients often struggle to differentiate between orthodontists and general dentists, which may affect their decisions regarding orthodontic care. Despite more than 85% of respondents believing that a dentist must be an orthodontic specialist to provide orthodontic treatment, only 64.3% correctly identified orthodontists as the more qualified professionals. Factors such as education level, age, and previous orthodontic treatment experience influenced awareness and preferences. Females, younger respondents, and those with higher education were more likely to prefer orthodontists. The findings emphasize the importance of public education to improve understanding of orthodontic qualifications.
Highlights:
- Awareness Gap: Many individuals cannot clearly distinguish between orthodontists and general dentists.
- Education’s Role: People with previous orthodontic treatment and higher educational attainment demonstrate greater awareness.
- Factors Influencing Choice: Doctor preference is significantly affected by age, sex, and education level, but not income.
- Preference Trends: Most patients prioritize expertise, choosing orthodontists over general dentists for treatment.
Need for Public Education: Addressing these misconceptions is crucial to ensuring informed decisions about orthodontic care.
Use of artificial intelligence in determination of bone age of the healthy individuals: A scoping review
Adeel Ahmed Bajjad, Seema Gupta, Soumitra Agarwal, Rakesh A. Pawar, Mansi U. Kothawade, Gul Singh
Published online: November 13, 2023 p95-102
Artificial intelligence (AI) is revolutionizing bone age determination, offering increased precision and efficiency compared to traditional manual methods. This review discusses how AI, including machine learning (ML) and deep learning (DL) approaches, is applied to assess bone age in healthy individuals, with tools like BoneXpert and neural networks at the forefront. Although AI has shown promise, especially for younger individuals and females, more comprehensive datasets and refined imaging technologies are needed for further improvement. Additionally, incorporating growth factors beyond bone structure could enhance AI model accuracy, underscoring the necessity of ongoing research.
Highlights:
- AI Precision: AI has demonstrated accuracy comparable to traditional assessments, reducing subjective errors.
- Data Limitations: More diverse datasets are required to improve model reliability across demographics.
- Demographic Sensitivity: AI models currently perform better for females and younger individuals.
- Advanced Imaging Potential: Techniques like MRI and 3D imaging could elevate bone age estimation.
