首页|Research from Faculty of Dental Medicine Provides New Data on Artificial Intelli gence (The Advent of Artificial Intelligence in Oral Pathology)

Research from Faculty of Dental Medicine Provides New Data on Artificial Intelli gence (The Advent of Artificial Intelligence in Oral Pathology)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from the Faculty of Dental Medic ine by NewsRx correspondents, research stated, “The medical and dental fields ar e experiencing a significant shift in approach thanks to the integration of arti ficial intelligence (AI).” The news journalists obtained a quote from the research from Faculty of Dental M edicine: “With a vast influx of patient data, there is a pressing need for sophi sticated software capable of organizing and preserving this information effectiv ely. The emergence of AI-driven models and computer vision techniques for identi fying patterns in clinical and histopathological images related to oral patholog y lesions holds promise for enhancing diagnostic accuracy and prognostic predict ions. While microscopic morphology remains the gold standard in diagnostic patho logy, its reliance on individual pathologists introduces variability. Consequent ly, AI presents a potential solution for achieving consistent and more precise d iagnoses. Moreover, by analyzing extensive data from the patients’ medical chart the artificial neural network could provide a presumptive diagnosis and an inva luable screening tool in predicting individual risk for oral pathology based on information regarding their risk factors, systemic diseases and conditions and c linical pathological data. Within oral and maxillofacial pathology, AI stands po ised to elevate diagnostic accuracy, tailor treatment, and ultimately enhance pa tient outcomes.”

Faculty of Dental MedicineArtificial I ntelligenceEmerging TechnologiesMachine LearningRisk and Prevention

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jul.3)