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Encyclopedia User Research Invitation: Share Your Insights on Academic Encyclopedias

Encyclopedia MDPI is conducting a targeted survey to identify the specific barriers hindering efficient research. We invite you to spend 3 minutes defining the priorities for our next generation of structured knowledge tools: 2026 Academic Encyclopedia Survey What This Study Explores As scholars’ approaches to accessing and engaging with knowledge evolve, we seek to better understand the role of structured resources in research and learning. Through this study, we aim to explore: What challenges scholars encounter when using structured knowledge entries; Where existing knowledge platforms may fall short of expectations; How structured knowledge resources can better support academic needs. The insights gained will help guide improvements to Encyclopedia MDPI. Contact Us If you have any questions or would like to participate in, please feel free to contact us at office@encyclopedia.pub. Kind regards,Encyclopedia Editorial Office

Announcement 19 Mar 2026

How Artificial Intelligence Could Improve Prognosis in Neuroendocrine Tumors

Gastro-entero-pancreatic neuroendocrine neoplasms are among the most biologically diverse tumors in oncology. These rare cancers arise throughout the digestive system and pancreas, and their clinical behavior can vary widely from one patient to another. Some tumors grow slowly over many years, while others progress much more aggressively. This variability makes prognosis particularly difficult, as patients with apparently similar diagnoses can experience very different clinical outcomes. Against this background, a recent review published in Cancers, titled "Artificial Intelligence for Prognosis of Gastro-Entero-Pancreatic Neuroendocrine Neoplasms", examines how artificial intelligence may help improve prognostic assessment in this complex disease. By analyzing clinical, imaging, and pathological information together, AI-based models could eventually support more individualized management for patients with these uncommon tumors. 1. Why Prognosis Remains Challenging The difficulty in managing GEP-NENs lies largely in their heterogeneity. Tumors can differ not only in anatomical location but also in biological behavior. A lesion in the pancreas may behave very differently from one in the small intestine, even when the two appear similar under standard pathological evaluation. Current prognosis usually depends on factors such as tumor grade, disease stage, primary site, and the Ki-67 proliferation index. These markers remain essential, but they do not always explain the full clinical picture. In practice, physicians often see patients whose disease behaves differently from what standard classifications would predict. Because treatment decisions often depend on expected disease course, improving prognostic accuracy remains an important goal. 2. The Limits of Traditional Models Traditional prognostic models are generally based on statistical methods that examine a limited number of variables at a time. While these tools provide useful clinical guidance, they can struggle to capture the complex interactions that influence tumor progression. Clinical outcomes in GEP-NENs may be shaped by multiple factors simultaneously, including imaging characteristics, molecular markers, prior treatments, and patient-specific health conditions. These relationships are rarely simple or linear. As a result, conventional prediction models may not fully reflect the biological complexity of the disease, which has encouraged interest in more advanced analytical approaches. 3. What Artificial Intelligence Can Add Artificial intelligence offers a different way to examine medical data. Instead of evaluating isolated variables, machine learning models can process large datasets and identify patterns across multiple sources of information at the same time. For neuroendocrine tumors, this may include: clinical history radiological imaging pathological findings molecular data By combining these data types, AI models may detect relationships that would be difficult to recognize using conventional analysis alone. This could help generate more refined estimates of disease progression and survival. Importantly, the goal is not to replace clinical judgment, but to provide additional information that may assist physicians in making more informed decisions. 4. Early Results from Prognostic Studies Several studies discussed in the review suggest that machine learning models may improve prognostic prediction in selected patient groups. Some early investigations found that machine learning approaches, including random survival forest models and neural networks, showed stronger predictive performance than conventional staging systems within specific datasets. These models were better able to account for non-linear relationships between clinical variables and patient outcomes. Although these findings are encouraging, the authors also emphasize that most available studies remain limited by: retrospective study design small patient cohorts single-center datasets lack of external validation Because of these limitations, AI-based models should still be considered investigational rather than established clinical tools. 5. Imaging as a Source of Hidden Information Medical imaging may become one of the most valuable areas for AI in GEP-NEN research. Patients often undergo CT, MRI, and PET imaging during diagnosis and follow-up, and these scans contain more information than can be captured through visual interpretation alone. Artificial intelligence can analyze subtle imaging features through radiomics, extracting quantitative data that may correlate with tumor aggressiveness or likely response to treatment. Rather than simply showing where a tumor is located, future AI-enhanced imaging may help reveal how the tumor is likely to behave. 6. A Possible Role in Digital Pathology Pathology remains central to the diagnosis of neuroendocrine neoplasms, but interpretation can sometimes vary among specialists, especially in rare tumor types. AI-assisted digital pathology may help improve consistency by identifying microscopic features associated with prognosis. By analyzing tissue patterns at high resolution, machine learning systems may uncover additional prognostic signals that are not always evident through routine examination. At present, these tools are still developing, but they may eventually complement standard pathological assessment. 7. The Challenges Still Ahead Despite the growing interest in AI, important barriers remain before these systems can be used routinely in clinical care. One major challenge is data quality. Because GEP-NENs are rare tumors, many institutions do not have enough patients to build large training datasets. Small datasets can limit the reliability of machine learning models. Another concern is transparency. Some AI systems can produce predictions without clearly showing how those predictions were generated. In medicine, this raises concerns because clinicians need to understand and trust the tools they use in patient care. The review also notes that ethical issues, including data privacy and algorithmic bias, must be addressed before AI can be more widely integrated into oncology practice. 8. Moving Toward More Personalized Care The long-term potential of artificial intelligence lies in personalization. Rather than relying only on broad disease categories, future models may help estimate prognosis at the level of the individual patient. With better validation, AI could eventually assist clinicians when considering: surveillance strategies surgical timing systemic therapy selection treatment sequencing For patients with neuroendocrine tumors, where clinical behavior can be highly unpredictable, more individualized prognostic tools could help improve decision-making throughout the course of care. 9. Conclusion Gastro-entero-pancreatic neuroendocrine neoplasms remain difficult to predict because of their biological diversity and variable clinical behavior. Traditional prognostic tools provide important information, but they do not always capture the full complexity of these tumors. Artificial intelligence offers a promising new direction by identifying patterns across clinical, imaging, and pathological data that may not be visible through conventional analysis. Although current evidence is still limited and further validation is needed, AI may eventually become a valuable decision-support tool in the management of patients with neuroendocrine tumors. For more information about topic, you can view the online video entitled "Artificial Intelligence for Prognosis of Gastro-Entero-Pancreatic Neuroendocrine Neoplasms".

Blog 28 Apr 2026

MDPI Video Service: Advancing Visual Scholarly Communication

Encyclopedia MDPI is thrilled to announce significant enhancements to its Academic Video Service, which aim to improve its quality, accessibility, and functionality. Since its launch, our video service has enabled numerous scholars to present their research in a dynamic and visually engaging format, greatly enhancing its visibility and impact. Due to the overwhelmingly positive reception this service has received, we have reached a point where the number of orders we are receiving exceeds our current capacity. In order to maintain the quality of these videos and continue optimizing the service, we have made the decision to introduce a fee. However, to ensure that this service is still a cost-effective option, we have set our prices significantly below the market average. 1. Highlights of the Upgrades to the Service Although the service will now be fee-based, we are committed to providing even more professional and comprehensive support, including the following: One-on-one video production guidance Personalized assistance to ensure your needs are fully met. Scriptwriting and English editing Expertly crafted narratives and professional English editing to ensure your research is presented clearly, accurately, and with impact. High-quality animations Visually engaging animations are created to simplify complex research and captivate your audience. Whiteboard Animations: Clean and minimalist, using hand-drawn illustrations to explain ideas step-by-step. Motion Graphics (MG) Animations: Cartoon Style: Bright, colorful, and approachable, ideal for making technical or scientific content more accessible and engaging. Hand-Drawn Style: Unique and artistic, adding a personal touch to your research while maintaining clarity and professionalism. Customized infographics (optional) We can also create tailored infographics to visually summarize key data or findings, enhancing the clarity and appeal of your video. Native voiceover Native speakers provide voiceovers to enhance the accessibility and reach of your research. Multiple rounds of revision To ensure your video accurately represents your work. Social media promotion Expanding your research's visibility and impact. 2. Why Choose Us? The Proven Impact of Video Abstracts Research shows that a well-crafted video abstract can significantly enhance the visibility and impact of your work. It has been shown to do the following: Increase paper views by 120% （Source: 10.1007/ s11192-019-03108-w） Boost citations by 20% （Source: Wiley Online Library） Improve journal rankings by 33% （Source: Research Square） Raise Altmetrics scores by 140% （Source: Research Square） Our Expertise in Academic Research Backed by MDPI, our experienced production team combines deep academic knowledge with creative excellence. We understand the nuances of scholarly communication and ensure that every frame accurately conveys the value of your research, meeting the highest standards of quality and precision. Collaborations with SCI Journals We have partnered with over 60 SCI journals to create exclusive video series, enhancing the dissemination and impact of published research. For example, our collaborations with Entropy, Remote Sensing, Nanomaterials , Animals , Nutrients, Foods , Sustainability, Cancers, etc., have helped authors achieve greater visibility and recognition for their work. Global visibility The videos are linked to your paper's DOI for maximum exposure. Available Video Services and Their Pricing Video Abstract (up to 5 minutes long): Summarizes the key findings, methodology, and significance of your research paper. Regular Price: 600 CHF Short Take (up to 2 minutes long): Uses original animations to explain the specific aspects of your research. Regular Price: 500 CHF Scholar Interview: A face-to-face discussion offering deeper insights into your publication. Regular Price: 400 CHF Scholar Profile: A brief overview of a scholar’s career, highlighting education, research focus, and key achievements. Regular Price: 500 CHF 3. Video Production Service If you want to see some examples of our videos, please visit https://encyclopedia.pub/video. If you would like to apply for the video service, please click https://encyclopedia.pub/video_service. 4. Others If you have any other questions, please contact office@encyclopedia.pub.

Announcement 14 Apr 2026

Best Video Abstract Awards

The Encyclopedia platform, together with the journals Biology and Nutrients, launches the Best Video Abstract Awards to increase the visibility and reach of published research and to inspire researchers to explore the power of visual storytelling. Video abstracts have become an increasingly important medium for scientific communication. By integrating narration, visualizations, animations, and experimental footage, they make complex research more accessible, engaging, and memorable. This initiative recognizes video abstracts that are not only scientifically rigorous but also creatively compelling and educational, thereby promoting broader dissemination and deeper community engagement. To learn more about the awards or to participate directly, please visit the event page via the links provided below. https://encyclopedia.pub/best-video-abstract-award 1. Event Duration 9 February 2026 – 2 February 2027 2. Awards Biology Best Video Abstract AwardOpen to video abstracts based on papers published in Biology between 1 January 2024 and 31 December 2025. This award will be granted to two video abstracts based on the evaluation of the Award Evaluation Committee. Nutrients Best Video Abstract AwardOpen to video abstracts based on papers published in Nutrients between 1 January 2024 and 31 December 2025. This award will be granted to two video abstracts based on the evaluation of the Award Evaluation Committee. Prize For each journal award, the winner will receive: CHF 500 A voucher waiving the Article Processing Charges (APCs) for one journal submission (subject to peer review, valid for one year) A free Academic Video Service production (no matter where the paper is published), valid for one year. An electronic certificate Participant Incentive All participants will receive a CHF 100 discount voucher for the Encyclopedia Academic Video Service. 3. Participation The event will be conducted in three stages. Submission Stage 9 February 2026 – 31 August 2026 Independent Submission Authors may create and submit video abstracts independently using their own tools and creative approach. Professional Support Option Authors who do not currently have a video abstract but intend to apply for the award may opt for the Academic Video Service, which offers a one-stop, end-to-end solution covering script development, animation, voiceover recording, and editing. Please submit your video abstract here: https://encyclopedia.pub/user/video_add?activity=b57ab0910b456a5e4eebd960867ce205 Or place your video service order here: https://encyclopedia.pub/user/video_service_order All video abstracts will be assessed by the editorial team for editorial suitability and overall quality. Submissions that meet the guidelines will be assessed equally. Voting Stage 1 November 2026 – 31 December 2026 Public voting will be conducted during this period. Voting results and video performance metrics, including views, likes, shares, and collections, will contribute to the final evaluation. Winner Announcement 2 February 2027 Final winners will be determined based on a combined assessment of public voting results and a comprehensive evaluation by the Award Evaluation Committee, which carries the primary weight in the final decision. Winners will be announced on the Encyclopedia platform and journal websites. 4. Others If you have any other questions, please contact office@encyclopedia.pub

Announcement 09 Feb 2026

Encyclopedia 2026 Outstanding Contributor Award

We are pleased to announce that the “Encyclopedia Outstanding Contributor Award” 2026 is now open for applications. We will award two outstanding contributors to the Encyclopedia platform (https://encyclopedia.pub/) and the Encyclopedia journal in 2026. After a thorough evaluation, the journal award committee, led by Editor-in-Chief Prof. Dr. Raffaele Barretta, will select all eligible contributors. The winners will be announced in March 2027. The Prize:–CHF 300;–An opportunity to publish one paper free of charge in the Encyclopedia journal before 31 December 2027, following peer review for each winner;–An electronic certificate. Application Deadline:15 January 2027. Document for Application:–Curriculum vitae/resume (please contact our office if you require a template of the form). Please send your curriculum vitae to our office before the deadline (encyclopedia@mdpi.com). The winners will be announced on the journal website in March 2027. Kind regards, Encyclopedia Editorial Office

Announcement 07 Apr 2026

See what people are saying about us

Shlomi Agmon

Encyclopedia Video provides potential readers with a tool to quickly understand what the work is about. That is important for casualreaders, whose time is thus spared, and for investedreaders, for whom it makes the decision to say "yes, I want to read the paper" much simpler.

School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem 9190401, Israel

Ignacio Cea

For the video abstracts, the papers and authors could gain more visibility and increase citations. Also, it means a more diverse and interesting way of communicating research, which is something valuable in itself.

Center for Research, Innovation and Creation, and Faculty of Religious Sciences and Philosophy, Temuco Catholic University

Melvin R. Pete Hayden

Thank the video production crew for making such a wonderful video. The narrations have been significantly added to the video! Congratulations on such an outstanding job of Encyclopedia Video team.

University of Missouri School of Medicine, United States

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