AI and Data Science in Biomedicine: Powering the Next Generation of Diagnostics and Therapies

Dear Colleagues,

The integration of Artificial Intelligence (AI) and Data Science into biomedicine has emerged as a transformative force, reshaping traditional paradigms of disease diagnostics, treatment methodologies, and patient care. As healthcare challenges grow increasingly complex, the need for innovative solutions that harness the power of large datasets, sophisticated algorithms, and computational models has never been more urgent. This Special Issue of Bioengineering aims to explore the convergence of AI, data science, and biomedicine, illuminating novel applications and profound implications for healthcare professionals, researchers, and patients alike.

AI and data science offer unprecedented opportunities to enhance the efficiency and accuracy of biomedicine. Machine learning techniques, particularly in deep learning, have shown remarkable capability for processing vast amounts of biomedical data—ranging from genomic sequences to clinical imaging. By analyzing these data types, AI can identify patterns and insights that are often imperceptible to human experts, leading to more accurate diagnostic tools, personalized treatment plans, and predictive models that anticipate patient outcomes. The continuous advancement in AI technologies provides a fertile ground for innovation that can redefine therapeutic strategies across various medical disciplines.

This Special Issue seeks to present cutting-edge research, reviews, and perspectives that highlight the applications of AI and data science in biomedicine. We invite contributions that demonstrate how AI and data science are actively engineering the future of biomedicine, turning complex data into actionable knowledge, and ultimately, into more precise, predictive, and personalized healthcare solutions for all.

Dr. Hongqing Yu
Prof. Dr. Yifan Zhao
Guest Editors

Manuscript Submission Information

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