AI-POWERED DIAGNOSTIC SUITE: INTEGRATING MULTI-MODAL MEDICAL IMAGING AND PREDICTIVE ANALYTICS

The rapid advancements in artificial intelligence (AI) have revolutionized the field of medical diagnostics, particularly through the integration of multimodal medical imaging and predictive analytics.This paper presents an AI-powered diagnostic suite that leverages deep learning and advanced data analytics to enhance disease detection, prognosis, and personalized treatment planning.By integrating various imaging modalities such as MRI, CT scans, ultrasound, and X-rays, the system provides a comprehensive and accurate assessment of patient health conditions.This approach not only improves diagnostic accuracy but also enhances clinical decision-making, reduces workload for healthcare professionals, and accelerates treatment interventions.The proposed framework is designed to be adaptable across various medical domains, including oncology, cardiology, and neurology.The study highlights the potential of AI-driven diagnostic suites in transforming modern healthcare by offering precise, efficient, and scalable diagnostic solutions.

Authors

Publication Details

Journal
International Research Journal of Education and Technology (IRJET).
Published
2024-11-29
DOI
https://doi.org/10.70127/irjedt.vol.7.issue03.1229
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

AI-POWERED DIAGNOSTIC SUITE: INTEGRATING MULTI-MODAL MEDICAL IMAGING AND PREDICTIVE ANALYTICS

L. R. Karlmarx
International Research Journal of Education and Technology (IRJET).
Artificial Intelligence in Healthcare
article

AI-POWERED DIAGNOSTIC SUITE: INTEGRATING MULTI-MODAL MEDICAL IMAGING AND PREDICTIVE ANALYTICS

L. R. Karlmarx
article en

Abstract

The rapid advancements in artificial intelligence (AI) have revolutionized the field of medical diagnostics, particularly through the integration of multimodal medical imaging and predictive analytics.This paper presents an AI-powered diagnostic suite that leverages deep learning and advanced data analytics to enhance disease detection, prognosis, and personalized treatment planning.By integrating various imaging modalities such as MRI, CT scans, ultrasound, and X-rays, the system provides a comprehensive and accurate assessment of patient health conditions.This approach not only improves diagnostic accuracy but also enhances clinical decision-making, reduces workload for healthcare professionals, and accelerates treatment interventions.The proposed framework is designed to be adaptable across various medical domains, including oncology, cardiology, and neurology.The study highlights the potential of AI-driven diagnostic suites in transforming modern healthcare by offering precise, efficient, and scalable diagnostic solutions.

International Research Journal of Education and Technology (IRJET).Vol. 6(11)
Openalex Percentile: Top 61%
Artificial Intelligence in Healthcare
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