Artificial Intelligence in Orthodontics: Current Trends and Future Directions
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Keywords

Artificial Intelligence
Orthodontics
Machine Learning
Deep Learning
Computer Vision
Diagnosis
Treatment Planning
Patient Outcomes
Future Directions

How to Cite

[1]
R. Reddy Yellu, Y. Kukalakunta, and P. Thunki, “Artificial Intelligence in Orthodontics: Current Trends and Future Directions”, Journal of Bioinformatics and Artificial Intelligence, vol. 4, no. 1, pp. 50–55, May 2024, Accessed: Nov. 23, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/15

Abstract

Artificial intelligence (AI) has revolutionized various industries, including healthcare, and orthodontics is no exception. This paper explores the current trends and future directions of AI in orthodontic treatments. AI technologies such as machine learning, deep learning, and computer vision are being increasingly applied to improve diagnosis, treatment planning, and patient outcomes in orthodontics. This paper reviews the latest research and developments in AI applications in orthodontics, discusses challenges and limitations, and proposes future directions for integrating AI into orthodontic practice.

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References

Jha, Rajesh K., et al. "An appropriate and cost-effective hospital recommender system for a patient of rural area using deep reinforcement learning." Intelligent Systems with Applications 18 (2023): 200218.

Pargaonkar, Shravan. "Bridging the Gap: Methodological Insights from Cognitive Science for Enhanced Requirement Gathering." Journal of Science & Technology 1.1 (2020): 61-66.

Pulimamidi, Rahul. "To enhance customer (or patient) experience based on IoT analytical study through technology (IT) transformation for E-healthcare." Measurement: Sensors (2024): 101087.

Sasidharan Pillai, Aravind. “Utilizing Deep Learning in Medical Image Analysis for Enhanced Diagnostic Accuracy and Patient Care: Challenges, Opportunities, and Ethical Implications”. Journal of Deep Learning in Genomic Data Analysis 1.1 (2021): 1-17.

Raparthi, Mohan. "AI Integration in Precision Health-Advancements, Challenges, and Future Prospects." Asian Journal of Multidisciplinary Research & Review 1.1 (2020): 90-96.

Raparthi, Mohan. "Deep Learning for Personalized Medicine-Enhancing Precision Health With AI." Journal of Science & Technology 1.1 (2020): 82-90.

Raparthi, Mohan. "AI-Driven Decision Support Systems for Precision Medicine: Examining the Development and Implementation of AI-Driven Decision Support Systems in Precision Medicine." Journal of Artificial Intelligence Research 1.1 (2021): 11-20.

Raparthi, Mohan. "Precision Health Informatics-Big Data and AI for Personalized Healthcare Solutions: Analyzing Their Roles in Generating Insights and Facilitating Personalized Healthcare Solutions." Human-Computer Interaction Perspectives 1.2 (2021): 1-8.

Raparthi, Mohan. "AI Assisted Drug Discovery: Emphasizing Its Role in Accelerating Precision Medicine Initiatives and Improving Treatment Outcomes." Human-Computer Interaction Perspectives 2.2 (2022): 1-10.

Raparthi, Mohan. "Robotic Process Automation in Healthcare-Streamlining Precision Medicine Workflows With AI." Journal of Science & Technology 1.1 (2020): 91-99.

Raparthi, Mohan. "Harnessing Quantum Computing for Drug Discovery and Molecular Modelling in Precision Medicine: Exploring Its Applications and Implications for Precision Medicine Advancement." Advances in Deep Learning Techniques 2.1 (2022): 27-36.

Shiwlani, Ashish, et al. "Synergies of AI and Smart Technology: Revolutionizing Cancer Medicine, Vaccine Development, and Patient Care." International Journal of Social, Humanities and Life Sciences 1.1 (2023): 10-18.

Raparthi, Mohan. "Quantum Cryptography and Secure Health Data Transmission: Emphasizing Quantum Cryptography’s Role in Ensuring Privacy and Confidentiality in Healthcare Systems." Blockchain Technology and Distributed Systems 2.2 (2022): 1-10.

Raparthi, Mohan. "Quantum Sensing Technologies for Biomedical Applications: Investigating the Advancements and Challenges." Journal of Computational Intelligence and Robotics 2.1 (2022): 21-32.

Raparthi, Mohan. "Quantum-Inspired Optimization Techniques for IoT Networks: Focusing on Resource Allocation and Network Efficiency Enhancement for Improved IoT Functionality." Advances in Deep Learning Techniques 2.2 (2022): 1-9.

Raparthi, Mohan. "Quantum-Inspired Neural Networks for Advanced AI Applications-A Scholarly Review of Quantum Computing Techniques in Neural Network Design." Journal of Computational Intelligence and Robotics 2.2 (2022): 1-8.

Raparthi, Mohan. "Privacy-Preserving IoT Data Management with Blockchain and AI-A Scholarly Examination of Decentralized Data Ownership and Access Control Mechanisms." Internet of Things and Edge Computing Journal 1.2 (2021): 1-10.

Raparthi, Mohan. "Real-Time AI Decision Making in IoT with Quantum Computing: Investigating & Exploring the Development and Implementation of Quantum-Supported AI Inference Systems for IoT Applications." Internet of Things and Edge Computing Journal 1.1 (2021): 18-27.

Raparthi, Mohan. "Blockchain-Based Supply Chain Management Using Machine Learning: Analyzing Decentralized Traceability and Transparency Solutions for Optimized Supply Chain Operations." Blockchain Technology and Distributed Systems 1.2 (2021): 1-9.

Tatineni, Sumanth. "Applying DevOps Practices for Quality and Reliability Improvement in Cloud-Based Systems." Technix international journal for engineering research (TIJER)10.11 (2023): 374-380.

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