ARTIFICIAL INTELLIGENCE IN PATHOLOGY: PRESENT AND FUTURE

Artificial intelligence is the future and its use in pathology can create a tremendous impact on health care in different aspects.Its use is being initiated in the field of pathology and is on the rise with a increasing acceptance.Pathology services will undergo a paradigm shift due to the implementation of computational pathology and the use of tools based on AI, which would increase the effectiveness and would be able to satisfy the demands of the precision medicine age. Moving AI models from research to clinical applications has been sluggish, notstanding their success. There may be too much distance and neglect between the clinical setting and self-contained research. The merge of AI technologies into pathology has significantly impacted diagnostic precision and speed. Digital pathology platforms equipped with machine learning algorithms enable pathologists to analyze large volumes of histological images with enhanced accuracy. These systems have demonstrated remarkable capabilities in identifying subtle morphological features indicative of various diseases such as cancerous lesions or infectious conditions. Moreover, AI-driven image analysis tools can assist pathologists in differentiating between benign and malignant tumors by quantifying cellular characteristics beyond human visual perception. Furthermore,AI-powered predictive models have the potential to refine prognostic assessments based on pathological findings. By leveraging vast datasets encompassing clinical outcomes and molecular profiles associated with specific diseases or tissue alterations, these algorithms can generate more tailored predictions regarding disease progression or treatment responsiveness. Through this approach,pathologists can offer more precise guidance on patient management while harnessing valuable insights from diverse sources for optimizing therapeutic intervention.The convergence of advanced image recognition techniques,virtual microscopy,and genomics data analysis could enable comprehensive profiling of individual disease phenotypes at an unprecedented level.In conclusion,AI technologies have already begun reshaping the landscapeof modern pathologypracticesthrough improved diagnostic capabilities,enriched prognostic insights,and envisaged pathways towards personalized healthcare delivery.The seamless integrationofAI-driven solutionsinto daily laboratory workflowswill undeniably propelpathologyintoa new era marked by heightened efficiencyand unparalleled precisionin diagnosticsand therapeuticsupport.

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Publication Details

Journal
Era s journal of medical research
Published
2024-12-01
DOI
https://doi.org/10.24041/ejmr2024.44
Primary Topic
AI in cancer detection
Type
article
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article

ARTIFICIAL INTELLIGENCE IN PATHOLOGY: PRESENT AND FUTURE

Saqib Ahmed
Era s journal of medical research
AI in cancer detection
article

ARTIFICIAL INTELLIGENCE IN PATHOLOGY: PRESENT AND FUTURE

Saqib Ahmed
article en

Abstract

Artificial intelligence is the future and its use in pathology can create a tremendous impact on health care in different aspects.Its use is being initiated in the field of pathology and is on the rise with a increasing acceptance.Pathology services will undergo a paradigm shift due to the implementation of computational pathology and the use of tools based on AI, which would increase the effectiveness and would be able to satisfy the demands of the precision medicine age. Moving AI models from research to clinical applications has been sluggish, notstanding their success. There may be too much distance and neglect between the clinical setting and self-contained research. The merge of AI technologies into pathology has significantly impacted diagnostic precision and speed. Digital pathology platforms equipped with machine learning algorithms enable pathologists to analyze large volumes of histological images with enhanced accuracy. These systems have demonstrated remarkable capabilities in identifying subtle morphological features indicative of various diseases such as cancerous lesions or infectious conditions. Moreover, AI-driven image analysis tools can assist pathologists in differentiating between benign and malignant tumors by quantifying cellular characteristics beyond human visual perception. Furthermore,AI-powered predictive models have the potential to refine prognostic assessments based on pathological findings. By leveraging vast datasets encompassing clinical outcomes and molecular profiles associated with specific diseases or tissue alterations, these algorithms can generate more tailored predictions regarding disease progression or treatment responsiveness. Through this approach,pathologists can offer more precise guidance on patient management while harnessing valuable insights from diverse sources for optimizing therapeutic intervention.The convergence of advanced image recognition techniques,virtual microscopy,and genomics data analysis could enable comprehensive profiling of individual disease phenotypes at an unprecedented level.In conclusion,AI technologies have already begun reshaping the landscapeof modern pathologypracticesthrough improved diagnostic capabilities,enriched prognostic insights,and envisaged pathways towards personalized healthcare delivery.The seamless integrationofAI-driven solutionsinto daily laboratory workflowswill undeniably propelpathologyintoa new era marked by heightened efficiencyand unparalleled precisionin diagnosticsand therapeuticsupport.

Era s journal of medical researchVol. 11(2)
Swami Rama Himalayan University (IN), Institute of Medical Sciences (IN)
Openalex Percentile: Top 76%
AI in cancer detection
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