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@article{194925,
        author = {A.Gokul Priya and K.MANIRAJ},
        title = {Application of Predictive Analytics and Machine Learning in Forecasting Orthodontic Treatment Outcomes Based on Clinical and Imaging Data},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6071-6077},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194925},
        abstract = {Orthodontic treatment planning is an important aspect in correcting dental and skeletal anomalies and enhancing oral function and facial aesthetics. Traditionally, orthodontists rely on analyzing patient clinical data and cephalometric X-ray images to assess jaw relationship and treatment procedures. However, orthodontic treatment outcome prediction is a difficult task because it involves various parameters such as patient age, skeletal structure, dental parameters, and growth pattern. Manual analysis is a tedious process and may cause variations in diagnosis due to individual clinical experience.  
To address these problems, this project proposes an intelligent system to predict orthodontic treatment outcome using various data mining techniques. The intelligent system will be able to predict orthodontic treatment outcome based on patient clinical parameters such as age, gender, dental parameters, and cephalometric X-ray images. Image processing techniques will be used to extract important parameters from patient X-ray images. Machine learning techniques will be used to analyze patient data to identify patterns related to treatment outcome. The proposed approach is useful for making data-driven decisions by orthodontists, which improves accuracy and speeds up the process of manual analysis.},
        keywords = {Predictive Analytics, Machine Learning, Orthodontic Treatment Prediction, Dental Image Processing, Cephalometric Analysis, Clinical Data Analysis, Artificial Intelligence in Healthcare.},
        month = {March},
        }