Revolutionizing Early Tumor Detection: Integrative AI Approaches for Accelerated and Accurate Diagnosis

Authors

  • Dr. Brajesh Kumar

Keywords:

Artificial Intelligence, Early Tumor Detection, Machine Learning, Deep Learning, Medical Imaging, Histopathology, Liquid Biopsy, Multi-omics, Biomarker Discovery, Clinical Decision Support

Abstract

Early diagnosis of tumors dramatically enhances survival rates and improves outcomes forcancer patients. However, conventional diagnostic modalities face significant challenges,including human error, inter-observer variability, and limitations in sensitivity, particularly in theearly stages of tumorigenesis.

References

Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S. Dermatologistlevel classification of skin cancer with deep neural networks. Nature. 2017;542(7639):115-118.

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Published

2024-06-20

How to Cite

Dr. Brajesh Kumar. (2024). Revolutionizing Early Tumor Detection: Integrative AI Approaches for Accelerated and Accurate Diagnosis . Journal of Computational Analysis and Applications (JoCAAA), 33(06), 2558–2568. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3463

Issue

Vol. 33 No. 06 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.