2379 research outputs found
Sort by
Ankle Health Assessment & Injury Risk: A Screening and Intervention Guide for Basketball and Volleyball Athletes
Get PDFMy capstone project, focuses on addressing the high rate of ankle injuries in basketball and volleyball. Since these sports involve frequent jumping, landing, and lateral movements, ankle injuries are not only common but often go untreated which increases the risk of long-term complications.
Through this project, I aim to develop an evidence-based ankle health assessment tool that evaluates range of motion, stability, strength, and proprioception. Based on an athlete’s score, I will provide a guide with targeted prehabilitation and rehabilitation exercises, as well as educational content on ankle health and injury prevention.
This project directly supports my goal of becoming a collegiate strength and conditioning coach. By creating a practical tool that I can use throughout my career, I will improve my ability to assess and address ankle health concerns in athletes. Ultimately, I hope this assessment will enhance performance and reduce injury risk to allow basketball and volleyball players to stay healthy and perform at their best.https://scholarworks.merrimack.edu/rcac_2025_posters/1159/thumbnail.jp
Augmenting large language models to predict social determinants of mental health in opioid use disorder using patient clinical notes
No full textObjective
Identifying social determinants of mental health (SDOMH) in patients with opioid use disorder (OUD) is crucial for estimating risk and enabling early intervention. Extracting such data from unstructured clinical notes is challenging due to annotation complexity and requires advanced natural language processing (NLP) techniques. We propose the Human-in-the-Loop Large Language Model Interaction for Annotation (HLLIA) framework, combined with a Multilevel Hierarchical Clinical-Longformer Embedding (MHCLE) algorithm, to annotate and predict SDOMH variables. Materials and Methods
We utilized 2636 annotated discharge summaries from the Medical Information Mart for Intensive Care (MIMIC-IV) dataset. High-quality annotations were ensured via a human-in-the-loop approach, refined using large language models (LLMs). The MHCLE algorithm performed multi-label classification of 13 SDOMH variables and was evaluated against baseline models, including RoBERTa, Bio_ClinicalBERT, ClinicalBERT, and ClinicalBigBird. Results
The MHCLE model achieved superior performance with 96.29% accuracy and a 95.41% F1score, surpassing baseline models. Training-testing policies P1, P2, and P3 yielded accuracies of 98.49%, 90.10%, and 89.04%, respectively, highlighting the importance of human intervention in refining LLM annotations. Discussion and Conclusion
Integrating the MHCLE model with the HLLIA framework offers an effective approach for predicting SDOMH factors from clinical notes, advancing NLP in OUD care. It highlights the importance of human oversight and sets a benchmark for future research
Using public bid as benchmark: A fair and transparent approach to managed public-private competition
No full textLeveraging Reddit in Academia
No full textThis study investigates how integrating Reddit into academic environments can enhance authentic learning experiences and strengthen information literacy skills. As a crowdsourced platform with diverse communities, Reddit provides access to a wide range of perspectives, hard-to-reach populations, and both qualitative and quantitative insights. While Reddit holds potential as a research tool, this article focuses on its application in supporting information literacy and authentic learning assignments. It examines the benefits and challenges of using Reddit in academic settings, highlighting practical applications such as project-based learning (PBL) and renewable assignments that cultivate critical thinking and collaborative learning. By incorporating Reddit into the classroom, educators can engage students in evaluating information critically, encourage collaboration, and promote deeper understanding through real-world applications, thereby positioning Reddit as a transformative tool for academic learning
Grassroots responses to extractivism: Case studies from around the world
No full textProfessor Mariko Frame co-edited this monograph and contributed the following chapters:
Introduction: Framing Socio-ecological Crises in the World-System: Living Histories and Deep Structures
Chapter 6: The Boeung Kak Lake Evictions and the Experience of Women in Cambodian Land Dispossessions
Chapter 7: Community-Led Activism in Cambodia\u27s Prey Lang Forest
Conclusion: Connecting Struggles: Final Reflections and Key Insight
