Exploring the Applications of Artificial Intelligence In Disease Screening and Diagnosis of Cancer Immunology

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Jaspreet Kaur; Fahmia Feroz

Exploring the Applications of Artificial Intelligence In Disease Screening and Diagnosis of Cancer Immunology

Authors: Jaspreet Kaur, Fahmia Feroz

Unique Paper ID: 176095
Volume: 11
Issue: 11
PageNo: 5319-5323

Keywords: T cells B cells immunotherapies cytokines CART cell therapy Allogeneic CAR T-cell therapy DNA macrophages radiation therapy monoclonal antibodies (single cell Immunoglobulins).

Abstract:
Cancer immunology is the fascinating area in which immune cells of our body mainly T cells and B cells produce cytotoxic compounds for to stop the unmanageable growth of tumor cells. In every day our body makes thousands of new cells for the proper surveillance of body when this process hurts due to some disturbances it leads cancer problem. In every country mostly females are affected by cancer as opposed to males. Behind this condition two reasons are responsible first one is they have low immunity power as comparison to men’s power and another one is obesity. Breast cancer and cervical cancer are more common in women’s and men’s globally have a higher chance in prostatic cancer and lungs and liver cancer. Through AI techniques we can easily diagnosed the all four stages of cancer. However, it concludes that meaningful insights can be extracted from tumor markers and lifestyle determinants by incorporating recent advancements such as CAR-T cell therapies, the GALLERI test, monoclonal antibody antigen tests, and cancer vaccines. In other words, integrating these innovations along with regular body checkups every six months—especially after chemotherapy—can significantly enhance early detection, monitoring, and personalized treatment strategies.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 5319-5323

Exploring the Applications of Artificial Intelligence In Disease Screening and Diagnosis of Cancer Immunology

Available:https://ijirt.org/article?manuscript=176095

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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