首页|University of Nebraska Medical Center Reports Findings in Artificial Intelligenc e (Multi-omics based artificial intelligence for cancer research)
University of Nebraska Medical Center Reports Findings in Artificial Intelligenc e (Multi-omics based artificial intelligence for cancer research)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Omaha, Nebraska , by NewsRx correspondents, research stated, "With significant advancements of n ext generation sequencing technologies, large amounts of multi-omics data, inclu ding genomics, epigenomics, transcriptomics, proteomics, and metabolomics, have been accumulated, offering an unprecedented opportunity to explore the heterogen eity and complexity of cancer across various molecular levels and scales. One of the promising aspects of multi-omics lies in its capacity to offer a holistic v iew of the biological networks and pathways underpinning cancer, facilitating a deeper understanding of its development, progression, and response to treatment. " Our news journalists obtained a quote from the research from the University of N ebraska Medical Center, "However, the exponential growth of data generated by mu lti-omics studies present significant analytical chAllenges. Processing, analyzi ng, integrating, and interpreting these multi-omics datasets to extract meaningf ul insights is an ambitious task that stands at the forefront of current cancer research. The application of artificial intelligence (AI) has emerged as a power ful solution to these chAllenges, demonstrating exceptional capabilities in deci phering complex patterns and extracting valuable information from large-scale, i ntricate omics datasets. This review delves into the synergy of AI and multi-omi cs, highlighting its revolutionary impact on oncology. We dissect how this confl uence is reshaping the landscape of cancer research and clinical practice, parti cularly in the realms of early detection, diagnosis, prognosis, treatment and pa thology. AdditionAlly, we elaborate the latest AI methods for multi-omics integr ation to provide a comprehensive insight of the complex biological mechanisms and inherent heterogeneity of cancer. FinAlly, we discuss the current chAllenges o f data harmonization, algorithm interpretability, and ethical considerations."
OmahaNebraskaUnited StatesNorth and Central AmericaArtificial IntelligenceCancerEmerging TechnologiesHealt h and MedicineMachine LearningOncology
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