The article "Radiomics Beyond the Hype: A Critical Evaluation Toward Oncologic Clinical Use" by Natally Horvat, MD, PhD; Nikolaos Papanikolaou, PhD; and Dow-Mu Koh, MD, provides a comprehensive evaluation of the potential and challenges of radiomics in oncology. Radiomics, which involves the extraction of high-dimensional quantitative data from medical images, has the potential to revolutionize cancer management by aiding in early tumor characterization, prognosis, risk stratification, treatment planning, response assessment, and surveillance. However, several challenges have hindered its clinical adoption and acceptability, including data standardization, infrastructure support, reproducibility, transparency, validation, usability, and trustworthiness. The authors outline the radiomics workflow, which includes clinical relevance, radiomics pipeline, and publication bias, and identify common mistakes and strategies to overcome them. Key challenges include the lack of multidisciplinary integration, inadequate study design, technical requirements, and the complexity of multistep processes. They emphasize the importance of engaging stakeholders early in the research process, ensuring data quality and standardization, and addressing issues such as imbalanced data and batch effects. The article also discusses the perspectives of patients, healthcare providers, and healthcare systems, highlighting the need for patient-centered care, provider education, and system priorities. Despite the challenges, the authors remain optimistic about the potential of radiomics, advocating for continued research and development to enhance its clinical utility and acceptability.The article "Radiomics Beyond the Hype: A Critical Evaluation Toward Oncologic Clinical Use" by Natally Horvat, MD, PhD; Nikolaos Papanikolaou, PhD; and Dow-Mu Koh, MD, provides a comprehensive evaluation of the potential and challenges of radiomics in oncology. Radiomics, which involves the extraction of high-dimensional quantitative data from medical images, has the potential to revolutionize cancer management by aiding in early tumor characterization, prognosis, risk stratification, treatment planning, response assessment, and surveillance. However, several challenges have hindered its clinical adoption and acceptability, including data standardization, infrastructure support, reproducibility, transparency, validation, usability, and trustworthiness. The authors outline the radiomics workflow, which includes clinical relevance, radiomics pipeline, and publication bias, and identify common mistakes and strategies to overcome them. Key challenges include the lack of multidisciplinary integration, inadequate study design, technical requirements, and the complexity of multistep processes. They emphasize the importance of engaging stakeholders early in the research process, ensuring data quality and standardization, and addressing issues such as imbalanced data and batch effects. The article also discusses the perspectives of patients, healthcare providers, and healthcare systems, highlighting the need for patient-centered care, provider education, and system priorities. Despite the challenges, the authors remain optimistic about the potential of radiomics, advocating for continued research and development to enhance its clinical utility and acceptability.