Journal Highlight : Artificial Intelligence in Oncology
The journal welcomes scholarly contributions related to the application of artificial intelligence, machine learning, and computational technologies in cancer research, diagnosis, treatment, and clinical oncology practice. This section focuses on research that advances data-driven oncology, improves diagnostic and therapeutic precision, enhances clinical decision-making, and supports innovation in personalized cancer care.
The journal encourages submissions in areas including Artificial Intelligence in Oncology, Machine Learning in Cancer Research, Deep Learning Applications, Computational Oncology, AI-Assisted Cancer Diagnostics, Radiomics and Imaging Analytics, Digital Pathology, Predictive Oncology Modeling, Natural Language Processing in Healthcare, and Clinical Decision Support Systems. Research related to Cancer Genomics and Bioinformatics, AI in Precision Oncology, Big Data Analytics in Cancer Research, Automated Tumor Detection, AI-Based Biomarker Discovery, and Robotics and Intelligent Healthcare Systems is also welcomed.
Submissions focusing on Early Cancer Detection Using AI, Treatment Response Prediction, Drug Discovery and Therapeutic Optimization, Cancer Risk Stratification, Personalized Oncology Approaches, AI in Radiation and Surgical Oncology, Workflow Automation in Oncology Practice, and Ethical and Regulatory Considerations in AI-Driven Healthcare are encouraged. The journal also welcomes studies evaluating the integration of artificial intelligence into clinical oncology workflows, population health studies, translational cancer research, and patient-centered cancer care.
Accepted manuscript types include Original Research Articles, Systematic Reviews, Meta-Analyses, Clinical and Computational Studies, Technology and Methodology Articles, Translational Research Articles, Case Reports, and Clinical Trial Reports that contribute to advancements in artificial intelligence and computational oncology.
Through this focus area, the journal aims to support research that advances intelligent oncology systems, improves cancer diagnosis and therapeutic precision, enhances personalized and evidence-based cancer care, and contributes to innovative digital transformation in oncology practice worldwide.
