Personalised Approach in Oncology to Improve the Efficiency of Patient Diagnosis and Treatment

According to the study's findings, applying individualised therapeutic approaches in combination with genomic, proteomic, metabolomic, and imaging technologies greatly improves the accuracy, efficacy, and safety of cancer diagnosis and treatment.

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Publication Details

Journal
Asian Pacific Journal of Cancer Prevention
Published
2025-12-01
DOI
https://doi.org/10.31557/apjcp.2025.26.12.4283
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Personalised Approach in Oncology to Improve the Efficiency of Patient Diagnosis and Treatment

Kristian Bechev, Rovena Tali, Szymon Suwala, Rushen Gafarov et al.
Asian Pacific Journal of Cancer Prevention
Radiomics and Machine Learning in Medical Imaging
article

Personalised Approach in Oncology to Improve the Efficiency of Patient Diagnosis and Treatment

Kristian Bechev, Rovena Tali, Szymon Suwala, Rushen Gafarov, Kyialbek Sakibaev
article en

Abstract

According to the study's findings, applying individualised therapeutic approaches in combination with genomic, proteomic, metabolomic, and imaging technologies greatly improves the accuracy, efficacy, and safety of cancer diagnosis and treatment.

Asian Pacific Journal of Cancer PreventionVol. 26(12)
University of Medicine Tirana (AL), National Academy of Sciences (US), Osh State University (KG), Medical University Plovdiv (BG), Nicolaus Copernicus University (PL), National Academy of Sciences of the Republic of Kyrgyzstan (KG), Samarkand State Medical Institute (UZ)
Good health and well-being
Openalex Percentile: Top 30%
Radiomics and Machine Learning in Medical Imaging
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Personalised Approach in Oncology to Improve the Efficiency of Patient Diagnosis and Treatment — Kristian Bechev, Rovena Tali, et al. · Asian Pacific Journal of Cancer Prevention (2025) | TGRS Research Map | TGRS