AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes DOI Creative Commons
David B. Olawade,

Navami Leena,

Eghosasere Egbon

et al.

Dentistry Journal, Journal Year: 2025, Volume and Issue: 13(5), P. 198 - 198

Published: April 30, 2025

Artificial Intelligence (AI) is rapidly transforming orthodontic care by providing personalized treatment plans that enhance precision and efficiency. This narrative review explores the current applications of AI in orthodontics, particularly its role predicting tooth movement, fabricating custom aligners, optimizing times, offering real-time patient monitoring. AI’s ability to analyze large datasets dental records, X-rays, 3D scans allows for highly individualized plans, improving both clinical outcomes satisfaction. AI-driven aligners braces are designed apply optimal forces teeth, reducing time discomfort. Additionally, AI-powered remote monitoring tools enable patients check their progress from home, decreasing need in-person visits making more accessible. The also highlights future prospects, such as integration with robotics performing procedures, predictive orthodontics early intervention, use printing technologies fabricate devices real-time. While offers tremendous potential, challenges remain areas data privacy, algorithmic bias, cost adopting technologies. However, continues evolve, capacity revolutionize will likely lead streamlined, patient-centered, effective treatments. underscores transformative modern promising advancing care.

Language: Английский

Overview of emerging electronics technologies for artificial intelligence: A review DOI Creative Commons
Peng Gao, Muhammad Adnan

Materials Today Electronics, Journal Year: 2025, Volume and Issue: unknown, P. 100136 - 100136

Published: Jan. 1, 2025

Language: Английский

Citations

0
Challenges for Ethics Review Committees in Regulating Medical Artificial Intelligence Research DOI

Alireza Esmaili,

Amirhossein Rahmani,

Abolhasan Alijanpour

et al.

Indian Journal of Surgical Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Language: Английский

Citations

0
Effect of AI-Based Pre-Hospital Health Education via QR Code on APAIS Scores in Patients with Breast Nodules: A Retrospective Study DOI Open Access
Guozhen Ma, C. Miao,

Pengjun Jiang

et al.

The Breast, Journal Year: 2025, Volume and Issue: unknown, P. 104481 - 104481

Published: April 1, 2025

Language: Английский

Citations

0
Comparative Analysis of Generative Artificial Intelligence Systems in Solving Clinical Pharmacy Problems：A Commentary on AI's Performance on the Clinical Pharmacy (Preprint) DOI

Lulu Li,

Aijuan Wang,

Pengqiang Du

et al.

Published: April 16, 2025

BACKGROUND In recent years, the implementation of artificial intelligence (AI) in health care is progressively transforming medical fields.However, there remains a gap between technological potential and practical application, necessitating establishment scientific evaluation system.Despite some existing research beginning to conduct clinical application assessments generative AI dialogue systems, these efforts are largely limited testing individual models on single tasks, lacking horizontal comparative analysis across multiple validation continuous decision chains real scenarios.As systems play an increasingly extensive role field Medicine Pharmacy, we need more explore this area. OBJECTIVE To systematically evaluate compare performance eight mainstream both domestic international, four core pharmacy practice scenarios: medication consultation, education, prescription review, case with pharmaceutical care. This study aims quantitatively assess their capabilities addressing common problems. METHODS Assessment questions were extracted from consultation clinic records, cases, pharmacist standardized training examination databases. Three researchers tested different same day using "inquiry prompts." A double-blind scoring design was employed, six experienced pharmacists backgrounds evaluating responses 0-10 scale dimensions: accuracy, rigor, applicability, logical coherence, conciseness, universality. Statistical used one-way variance (ANOVA) score differences comparison tests for significant results, intraclass correlation coefficient (ICC) calculations inter-rater consistency.Systematic descriptive evaluations AI-generated also conducted. RESULTS DeepSeek-R1 demonstrated best overall all task categories. Qwen, GPT-4o, Claude-3.5-Sonnet, Gemini-1.5-Pro performed slightly inferior DeepSeek-R1. Doubao Kimi showed inconsistent performance, while ERNIE Bot poorest. Comprehensive indicated that still have certain limitations should be as reference tools rather than independent decision-making bases. Inter-rater consistency good agreement (ICC>0.75) review. However, lowest level (ICC=0.70) observed assessing conciseness care, reflecting cognitive among raters regarding standards complex issues. CONCLUSIONS The model demonstrates supportive tool practice. overall, current require systematic improvement refinement ability handle multidimensional CLINICALTRIAL none

Language: Английский

Citations

0
AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes DOI Creative Commons
David B. Olawade,

Navami Leena,

Eghosasere Egbon

et al.

Dentistry Journal, Journal Year: 2025, Volume and Issue: 13(5), P. 198 - 198

Published: April 30, 2025

Artificial Intelligence (AI) is rapidly transforming orthodontic care by providing personalized treatment plans that enhance precision and efficiency. This narrative review explores the current applications of AI in orthodontics, particularly its role predicting tooth movement, fabricating custom aligners, optimizing times, offering real-time patient monitoring. AI’s ability to analyze large datasets dental records, X-rays, 3D scans allows for highly individualized plans, improving both clinical outcomes satisfaction. AI-driven aligners braces are designed apply optimal forces teeth, reducing time discomfort. Additionally, AI-powered remote monitoring tools enable patients check their progress from home, decreasing need in-person visits making more accessible. The also highlights future prospects, such as integration with robotics performing procedures, predictive orthodontics early intervention, use printing technologies fabricate devices real-time. While offers tremendous potential, challenges remain areas data privacy, algorithmic bias, cost adopting technologies. However, continues evolve, capacity revolutionize will likely lead streamlined, patient-centered, effective treatments. underscores transformative modern promising advancing care.

Language: Английский

Citations

0