Published Research
Explore various AI-related research publications by Loyola faculty and the AI Business Consortium's online publication, The AI Edge.
Featured Articles

Featured Research | August 2026
Trust Calibration and Patient Decision in AI-Supported Infectious Disease Triage
See how trust in AI shapes whether patients accept or reject its recommendations in time-sensitive infectious disease triage.

Featured Research | August 2026
Trusting to Continue or Resist: How AI Governance Shapes AI-Based Emotional Support Usages Across Countries
Learn how AI governance and trust shape whether people embrace or resist AI-based emotional support across countries.
More Articles
August 2026
- AI Edge: Q3
Explore perspectives on institutional AI stewardship, emerging requirements for stablecoin issuers, and a new legal practice at the intersection of AI regulation and engineering.
July 2026
- Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings
Explore how LLMs can build more effective taxonomies of AI skills from job data, showing that carefully filtered inputs, not more data, lead to clearer and more meaningful results. - LLM-Assisted Formalization for Deterministic Detection of Statutory Inconsistency in Tax Law
Learn how combining LLMs with symbolic logic enables consistent, transparent detection of legal inconsistencies, overcoming the limits of probabilistic AI in complex tax law.
June 2026
- Can LLMs Write Correct TLA+ Specifications? Evaluating Natural-Language-to-TLA+ Generation
This paper explores how emerging AI architectures are making systems more reliable, transparent, and ready for real-world use.
May 2026
- AI Edge: Q2
AI is everywhere—but making it work is harder than it looks. These articles explore how AI can miss the human behind the data, why most agent initiatives stall before production, and how new approaches are making AI decisions more consistent and transparent. - Explainable Multimodal Deep Learning Models for Variable-Length Sequences in Critically Ill Patients
See how new biomedical informatics research on how data-driven methods can support health and clinical research.
April 2026
- Toward Experiential Training Program for AI Security and Privacy Practitioners
From the 2025 CAE-CD Symposium, this highlight features Loyola research—including an extended abstract from Eric Chan-Tin—focused on experiential training to strengthen AI security, privacy, and real-world risk mitigation. - LogosKG: Hardware-Optimized Scalable and Interpretable Knowledge Graph Retrieval
Explore how LogosKG makes large-scale knowledge graph retrieval more scalable, efficient, and interpretable. - Intro to Statistics in Criminal Justice and Criminology: A Practical Approach to Calculating, Using, and Interpreting Data
A practical, plain-English intro to stats for criminal justice and criminology. Learn to calculate, interpret, and use data with confidence. - Molecular Contrastive Learning with Graph Attention Network (MoCL-GAT) for Enhanced Molecular Representation
A new graph-based approach to stronger molecular representations—see what improves and why it matters. - DTA-GNN: A Toolkit for Constructing Target-Specific Drug–Target Affinity Datasets and Training Graph Neural Networks
A hands-on toolkit for building drug–target affinity datasets and training GNN models—ready to plug into your workflow. - Now's the Time: Computer Science Must Evolve to Emphasize Software and Systems Engineering with AI
Why computer science education needs to shift from “learning to code” to engineering AI-enabled systems. - Transforming FHIR into an OWL Knowledge Graph for Schema-Grounded Natural-Language Querying and Exploratory Data Analysis
Turning complex clinical records into a knowledge graph so data is easier to search, explore, and analyze.
March 2026
- AI Edge: Q1
Explore perspectives on institutional AI stewardship, emerging requirements for stablecoin issuers, and a new legal practice at the intersection of AI regulation and engineering. - The Digital Scholar: Artificial Intelligence in Social Work Research
Read how AI can support social work research while raising important questions about ethics and responsible use. - An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process
See how scientists are reusing pre-trained deep learning models across the research process. - A Novel Patient-Specific Solution for Merkel Cell Carcinoma in High-Dose-Rate Brachytherapy
A 3D-printed, patient-specific hand applicator made complex HDR brachytherapy practical—see the workflow and 1-year outcome.
February 2026
- Machine Learning Models Powered by Emergency Medical Services Data Enhance Stroke Triage in Prehospital Settings
See how machine learning models using real-time EMS data can improve early stroke detection. - From Moderation to Mediation: Can LLMs Serve as Mediators in Online Flame Wars?
Can LLMs cool down online fights? See what happens when models try to mediate, not just moderate. - Machine Learning Models Powered by Emergency Medical Services Data Enhance Stroke Triage in Prehospital Settings
Faster stroke triage starts in the ambulance. See how EMS data + ML boosts early detection. - Uncovering eHealth Engagement Patterns Through Latent Class Analysis and SHAP: A Data Mining Perspective on Telehealth Access
Telehealth isn’t one-size-fits-all. Explore four digital engagement profiles—and what predicts access. - Predicting Employees' Organizational Citizenship Behavior: A Comparative Study Using AI Techniques
Can AI predict who goes the extra mile at work? This study shows how HR can use data-driven models to forecast and foster organizational citizenship behavior.
January 2026
- Toward AI Agent Behavior Research: A Behavioral Science Approach to Machine Decision-making in AI Interaction Platform
See what happens to attention when only AI agents run the platform—and all optimize the same way. - Scaling Biomedical Knowledge Graph Retrieval for Interpretable Reasoning: Applications to Clinical Diagnosis Prediction
Turn billion-edge biomedical graphs into fast, interpretable diagnostic clues with LogosKG. - AI Nudging and Decision Quality: Evidence from Randomized Experiments in Online Recommendation Setting
How do AI “nudges” like Amazon’s Choice shape what we buy, how confident we feel, and how much we trust recommendations?
December 2025
- AI Edge: Q4
A quick, practical scan of what’s working in AI right now—beyond the hype: smarter strategy, more reliable results, and audit-ready compliance. - Predicting Failures of LLMs to Link Biomedical Ontology Terms to Identifiers: Evidence Across Models and Ontologies
Why do LLMs miss ontology IDs? This study pinpoints the features that predict failure across models and ontologies. - Healthcare AI's Unlearned Intermediaries
Explore how deference to FDA processes can quietly block injured patients from recovering in AI device cases. - AI in Medication Management and Drug Dosing in Critical Care
See how AI is being used to optimize medication dosing in intensive care. - Evaluating the Use of LLMs to Answer Patient-Facing Clinical Trial Questions
Not all LLMs are equal: learn why rigorous testing is critical before letting AI talk to patients. - 3D Shape Cues Affect Human and Artificial Recognition Systems Differently
Do humans and neural networks really “see” the same object? Shape, texture, and 3D cues tell a different story. - AI Foundation Model Automates Cryo-EM Structure Determination
Meet Cryo-IEF: a foundation model that automates cryo-EM structure determination. - Human at the Center: A Framework for Human-Driven AI Development
When humans and AI work together, performance often drops. See how rethinking design can turn that around.
November 2025
- An Interactive Agentic HPC Tutor for Lesson Planning, Teaching, and Assessment
From prompts to parallel programming. Meet an interactive, multi-agent HPC tutor built for classrooms and labs. - Bridging the Gap: AI Technology Competence in Contemporary Legal Education
Are tomorrow’s lawyers ready for AI—or already behind?
October 2025
- SysLLMatic: Large Language Models are Software System Optimizers
From microbenchmarks to full apps, discover how SysLLMatic scales LLM code optimization to production-size software. - Extracting O*NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data
A new natural language processing toolkit, funded by the Washington Center for Equitable Growth, extracts over 10 billion data points from 155 million job ads, transforming the chaos of online postings into a powerful, transparent, public-use dataset for analyzing the modern labor market.
September 2025
- The Association of Area Deprivation Index and Blood Pressure Control and Therapeutic Inertia Among Older Adults with Hypertension
Discover how neighborhood deprivation shapes hypertension care in older adults—finding modest links to treatment inertia, even when blood pressure control itself shows no clear association. - Prior Knowledge Shapes Success When Large Language Models Are Fine-Tuned for Biomedical Term Normalization
Research uncovers a "reactive middle zone" where an LLM's existing knowledge determines if fine-tuning will succeed, revealing the secret to a model's ability to learn new biomedical associations. - Artificial Intelligence in the Management of Leukemia
AI can already help detect leukemia—can it also help prevent relapse? - AI-Driven Systems in MTSS: Potential Opportunities and Challenges
As schools face limited resources, AI offers both promise and pitfalls for implementing MTSS. Learn how educators and school psychologists can harness AI responsibly to support every learner.
August 2025
- AI Edge: Q3
AI is transforming work through new tools, cloud infrastructure, and automation while highlighting that human relationships, collaboration, and creativity remain essential in the workplace.
July 2025
- Strengthening Scientific Integrity: Digital Forensics for Biomedical Research Imaging
See how digital forensics is exposing manipulation in biomedical research images. - Use of a Deep Learning Neural Network to Generate Bone Suppressed Images for Markerless Lung Tumor Tracking
A deep learning model generates synthetic bone-suppressed images, enabling accurate markerless lung tumor tracking with a single X-ray exposure. - Towards Human-Centered AI: The Role of Social Sciences
The social sciences are essential, not only for analyzing the transformations brought by Artificial Intelligence but primarily for guiding its future development to be human-centered, focusing on its impact on interpersonal relations, social equality, and political regimes/public policy.
June 2025
- Climate Media Amidst Technopolitical Change
Climate media research must move beyond outdated frameworks to address the complex, shifting realities of modern media and politics.
May 2025
- AI Edge: Q2
From AI inspired by human movement to data-driven retail and the generational shift shaping corporate innovation, these three articles reveal how businesses are adapting—and thriving—in an intelligent, fast-changing world. - Improving the Reproducibility of Deep Learning Software
Reproducibility remains a critical challenge in deep learning. This study offers practical guidelines and a case study showing how researchers can close the gap between innovation and reliable replication. - Preprocessing of Physician Notes by LLMs Improves Clinical Concept Extraction Without Information Loss
LLMs can clean up messy physician notes—boosting concept extraction by 50% without losing key clinical info.
April 2025
- Artificial Intelligence and Academic Integrity: Legislate or Educate?
Are AI rules enough—or do we need to teach better? - Is AI Revolutionizing Climate Change Education?
Learn how ChatGPT’s climate responses often promote passive learning, vague concern, and limited transparency—raising questions for educators and students alike.
February 2025
- AI Edge: Q1
From workforce disruption to ethical dilemmas, AI is reshaping industries at an unprecedented pace. This issue explores the evolving job landscape, the urgent need to address AI bias, and the latest advancements in automation. Discover what these shifts mean for businesses, workers, and the future of technology-driven decision-making.
January 2025
- Ethical Concerns in Contemporary VR and Frameworks for Pursuing Responsible Use
Discover the ethical gaps in Virtual Reality and how existing frameworks—from IRB to care ethics—can be synthesized into a new model for responsible VR use. - The TRIPOD-LLM Reporting Guideline for Studies Using Large Language Models
Bringing order to the chaos of LLM-in-healthcare studies—meet TRIPOD-LLM. - In Moderation: Automation in the Digital Public Sphere
Explore the Principle of Epistemic Resilience, a new approach to guiding digital platforms' content policies, with insights on how moderation and algorithm changes can foster healthy debate.
December 2024
- AI Edge: Q4
From overcoming adoption challenges to reshaping the workforce, this issue delves into the transformative power of AI. Explore practical strategies for scaling solutions, ethical considerations for the future of work, and hiring trends shaping AI roles. Whether you're navigating implementation or keeping pace with industry demands, these insights offer a roadmap to thrive in the AI-driven era. - Humans Outside the Loop
AI may seem autonomous, but human choices shape it at every step—yet when things go wrong, current laws offer little recourse. This piece reveals why today’s liability systems fall short and what could change. - Noise2Inverse for 3D Low-Dose Cone-Beam Computed Tomography
Extending Noise2Inverse to 3D CBCT volumes, this deep learning approach reduces noise in low-dose scans, improving image quality without extra radiation exposure.
November 2024
- The Routledge Handbook of Artificial Intelligence and Philanthropy
A comprehensive guide to AI and philanthropy, this handbook explores ethical AI integration, philanthropy's role in shaping AI, and practical case studies, fostering collaboration and advancing research.
October 2024
- Revealing the Limits of Cybersecurity Law for Healthcare AI
Healthcare tech holds sensitive data, but weak cybersecurity laws leave it exposed. - Calculation of Alpha Particle Single-Event Spectra Using a Neural Network
A neural network accurately predicts alpha-particle single-event spectra, streamlining microdosimetry calculations across diverse cell and tissue configurations.
September 2024
- AI Employment Interviews: Examining Limitations, Biases, and Perceptions
What happens when an algorithm decides if you get the job? - The New EU–US Data Protection Framework’s Implications for Healthcare
The new U.S.-EU Data Privacy Framework aims to ease health data transfers—but gaps and stricter EU rules may still hinder cross-border healthcare and research.
August 2024
- AI Edge: Q3
Explore how the latest advancements in AI and machine learning are transforming industries across the board. From aligning strategic investments to drive long-term profitability, to the cutting-edge innovations in financial services, and the revolutionary impact of Gen AI-powered Digital Knowledge Workers™ in manufacturing—discover how these technologies are enhancing decision-making, boosting productivity, and driving the next wave of business success.
May 2024
- AI Edge: Q2
Topics include generative AI's impact on manufacturing design, maintenance, and quality control; the role of objective functions in defining AI's capabilities; and how large language models are transforming AI with autonomous agents for improved decision-making and customer experiences. - Synthetic Realities and AI-Generated Contents
When AI can fake anything, how do we trust what we see? - Prescribing Exploitation
AI-powered medical devices can quietly exploit patients, especially when reliance is unavoidable and data collection is constant. This piece argues for legal safeguards to protect users from excessive harm.
April 2024
- What’s Democratic About ‘Democratizing AI’?
By invoking the language of democracy without considering how best to ensure collective governance, tech companies fail at offering a truly democratic AI. - A Computer Vision Solution to Cross-cultural Food Image Classification and Nutrition Logging
What if snapping a photo could give anyone, anywhere, an accurate nutrition log—no matter the cuisine? - Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam Computed Tomography Reconstruction
A large-scale benchmark study reveals how deep learning can enhance low-dose 3D CT reconstructions, cutting radiation without compromising image quality. - Low Dose CBCT Denoising Using a 3D U-Net
A 3D deep learning approach effectively denoises low-dose CBCT scans, reducing radiation exposure while preserving image quality.
March 2024
- AI Edge: Q1
Topics include: Retrieval-Augmented Generation (RAG) models and their potential for various industries; the transformative role of AI in supply chain management, and machine learning insights for non-machine learning engineers. - Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data
See how synthetic clinical data generated by language models could strengthen clinical NLP performance in healthcare research.
2023 Research
July 2023
AI Edge: Q3
Topics include: how AI is transforming retail supply and demand planning; ways generative AI can be leveraged in the insurance industry and executive search; and a consumer perspective of health care and AI.
Prostate Segmentation Accuracy Using Synthetic MRI for High-Dose-Rate Prostate Brachytherapy Treatment Planning
A generative AI model creates synthetic MRI from CT scans, enabling accurate prostate segmentation for high-dose-rate brachytherapy even when MRI is unavailable.
October 2023
AI Edge: Q4
Topics include: how successful structuring of AI can improve productivity, protocols for ChatGPT use in the classroom; six points to assist firms in the structure and rollout of AI; and the potential need for governance, risk, and compliance solutions as AI regulation increases.
Dosimetric and Workflow Impact of Synthetic-MRI Use in Prostate High-Dose-Rate Brachytherapy
Synthetic MRI generated from CT can streamline prostate HDR brachytherapy planning, maintaining accurate target coverage while reducing workflow complexity and registration errors.
Holistic Evaluation of Language Models
HELM enhances transparency in language models through comprehensive evaluation across scenarios and metrics, benchmarking 30 models to expose trade-offs, improve coverage, and share findings openly for community collaboration.
December 2023
Ethical and Social Challenges, the Frontier of AI
AI can transform lives with immense benefits but risks amplifying societal issues if not carefully designed.
2022 Research
November 2022
Adopting a Dynamic AI Price Optimisation Model to Encourage Retail Customer Engagement
Technology innovation, changing consumer preferences and behaviours and competition compel successful enterprises to embrace change. Nowhere are these pressures more acute than in the retail industry and, in particular, for those engaged in the sale of fashion merchandise.
June 2022
Development and Multimodal Validation of a Substance Misuse Algorithm for Referral to Treatment Using Artificial Intelligence (SMART-AI)
A new AI algorithm accurately screens hospital patients for multiple types of substance misuse using just the first 24 hours of clinical notes.
2021 Research
December 2021
Beyond the "Black Box"
AI's "black box" hides behind trade secrets. Discover how system and process disclosure can unlock transparency and fairness without revealing core algorithms.
November 2021
AI’s Legitimate Interest: Towards a Public Benefit Privacy Model
Health privacy laws are failing to keep pace with AI. Explore a new model that protects individuals while unlocking health data's full potential for community well-being.
August 2021
Medical Device Artificial Intelligence: The New Tort Frontier
AI medical devices promise health breakthroughs but pose new safety risks. Discover how current laws fall short and what's needed for patient protection in this new tort frontier.
March 2021
Balancing the Halo: Data Surveillance Disclosure and Algorithmic Opacity in Smart Hearing Aids
Smart hearing aids: powerful, but data collection is opaque, limiting user control. This article reveals the problem and proposes solutions for informed choice.
January 2021
Legal Opacity: Artificial Intelligence’s Sticky Wicket
AI's "black box" isn't just technical; it's also legally opaque, creating a dual barrier to true transparency.
2020 Research
September 2020
Medical Imaging and Privacy in the Era of Artificial Intelligence: Myth, Fallacy, and the Future
AI transforms medical imaging, but existing privacy laws like HIPAA can't protect uniquely identifiable digital images. We need new consent models to responsibly harness AI's diagnostic power.
May 2020
Healthcare Privacy-AI Impasse
How has technology changed the patient-physician relationship? Dive into the healthcare privacy-AI impasse and its impact on your medical data.
2018 Research
September 2018
Deus ex Machina: Regulating Cybersecurity and Artificial Intelligence for Patients of the Future
Uncover how the "Deus ex Machina" of AI promises medical miracles, but necessitates urgent regulatory action to safeguard future patients from unforeseen cybersecurity risks.
March 2018
Regulating the Internet of Things: Discrimination, Privacy, and Cybersecurity in the AI Age
IoT and AI introduce new privacy and cybersecurity risks to everyday products. This article explores current regulatory gaps and proposes a balanced legal framework to protect consumers and foster innovation.