OMICS and Nuclear Medicine

Omics, in particular,and radiomics are complementary approaches that provide a very comprehensive, multi-layered view of a disease, particularly cancer. By cCombining genetic, molecular, and imaging data with machine learning, they enhances the diagnostic and prognostic capabilities of nuclear medicine, and hence advancesing the field of personalized treatment. Notably, a substantial amount of research has explored the utility of nuclear medicine radiomics in the context of digestive system tumors. It is a very optimistic and promising field of research that maximizes the diagnostic and prognostic yield of existing images. This development is expected to accelerate workflow and enhance the precision of diagnosis and decision support prediction capacity, thus establishing a link between nuclear medical imaging and personalized diagnosis and treatment. The clinical impact of the human genome; the most popular OMICS- suffix carrier includes improved diagnostics for rare and complex diseases, more targeted and personalized treatments, and the development of new therapies like gene therapy. This knowledge allows for better prediction of disease risk, development of new drugs and vaccines, and a deeper understanding of how genetic variations influence health and disease, ultimately revolutionizing medical practice. To translate radiomics into clinical practice, higher publication standards and standardization of workflows are needed.

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Publication Details

Journal
The Egyptian Journal Nuclear Medicine
Published
2025-12-01
DOI
https://doi.org/10.21608/egyjnm.2025.433741.1134
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

OMICS and Nuclear Medicine

Khalid Taalab
The Egyptian Journal Nuclear Medicine
Radiomics and Machine Learning in Medical Imaging
article

OMICS and Nuclear Medicine

Khalid Taalab
article en

Abstract

Omics, in particular,and radiomics are complementary approaches that provide a very comprehensive, multi-layered view of a disease, particularly cancer. By cCombining genetic, molecular, and imaging data with machine learning, they enhances the diagnostic and prognostic capabilities of nuclear medicine, and hence advancesing the field of personalized treatment. Notably, a substantial amount of research has explored the utility of nuclear medicine radiomics in the context of digestive system tumors. It is a very optimistic and promising field of research that maximizes the diagnostic and prognostic yield of existing images. This development is expected to accelerate workflow and enhance the precision of diagnosis and decision support prediction capacity, thus establishing a link between nuclear medical imaging and personalized diagnosis and treatment. The clinical impact of the human genome; the most popular OMICS- suffix carrier includes improved diagnostics for rare and complex diseases, more targeted and personalized treatments, and the development of new therapies like gene therapy. This knowledge allows for better prediction of disease risk, development of new drugs and vaccines, and a deeper understanding of how genetic variations influence health and disease, ultimately revolutionizing medical practice. To translate radiomics into clinical practice, higher publication standards and standardization of workflows are needed.

The Egyptian Journal Nuclear MedicineVol. 31(2)
Military Medical Academy (RS), Military Medical Academy (EG)
Openalex Percentile: Top 30%
Radiomics and Machine Learning in Medical Imaging
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