Overview
This is a call for papers for a forthcoming volume in the Lecture Notes in Artificial Intelligence series, focusing on the integration of artificial intelligence and machine learning within the domain of digital pathology. This initiative presents a significant opportunity for researchers to contribute to a growing field that intersects healthcare and advanced computational techniques.
Background & Relevance
Digital pathology is an evolving field that leverages technology to enhance the analysis and interpretation of pathological data. The integration of AI and machine learning into this area promises to improve diagnostic accuracy, streamline workflows, and ultimately enhance patient outcomes. As the healthcare industry increasingly adopts digital solutions, the relevance of AI in pathology becomes paramount, making this call for papers timely and crucial for advancing research and application.
Key Details
- Submission Deadline: End of the year 2023
- Publisher: Springer
- Volume: Lecture Notes in AI
- Focus Area: AI and Machine Learning applications in Digital Pathology
- Link for Submission: Springer LNAI Call for Papers
Eligibility & Participation
This call for papers is open to researchers, practitioners, and academics who are engaged in the fields of AI, machine learning, and digital pathology. Contributions are welcomed from those who can provide insights, research findings, or innovative applications that advance the field.
Submission or Application Guidelines
- Review the submission guidelines provided on the Springer link.
- Prepare your manuscript according to the specified format.
- Submit your paper through the designated submission platform before the deadline.
Additional Context / Real-World Relevance
The application of AI and machine learning in digital pathology not only enhances the capabilities of pathologists but also contributes to the broader goals of personalized medicine. By improving diagnostic processes and enabling more accurate disease predictions, this research area holds the potential to transform patient care and healthcare delivery.
Conclusion
Researchers and practitioners are encouraged to explore this opportunity to share their findings and innovations in AI and machine learning as applied to digital pathology. Contributions to this volume will play a vital role in shaping the future of this interdisciplinary field. Interested individuals should prepare their submissions in accordance with the guidelines and submit them by the end of the year.
Category: CFP & Deadlines
Tags: ai, machine learning, digital pathology, springer, healthcare, computer vision, medical imaging, data analysis
