OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 25.03.2026, 19:15

Dan Nguyen

261 Arbeiten4.263 Zitationen

University of North Texas · US

Relevante Arbeiten

Meistzitierte Publikationen im Bereich Gesundheit & MedTech

An introduction to deep learning in medical physics: advantages, potential, and challenges

2020 · 182 Zit. · Physics in Medicine and Biology

Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency

2022 · 69 Zit. · Physics in Medicine and Biology

Advances in Automated Treatment Planning

2022 · 40 Zit. · Seminars in Radiation Oncology

Deep Learning–Based COVID-19 Pneumonia Classification Using Chest CT Images: Model Generalizability

2021 · 30 Zit. · Frontiers in Artificial Intelligence

Artificial intelligence guided physician directive improves head and neck planning quality and practice Uniformity: A prospective study

2023 · 12 Zit. · Clinical and Translational Radiation Oncology

Evaluating the performance of ChatGPT on dermatology board-style exams: A meta-analysis of text-based and image-based question accuracy

2025 · 5 Zit. · Journal of the American Academy of Dermatology

A sensitivity analysis of probability maps in deep‐learning‐based anatomical segmentation

2021 · 5 Zit. · Journal of Applied Clinical Medical Physics

Artificial Intelligence Guided Physician Directive Improves Head and Neck Planning Quality and Practice Uniformity: A Prospective Study

2021 · 3 Zit. · International Journal of Radiation Oncology*Biology*Physics

Uncertainty estimations methods for a deep learning model to aid in clinical decision-making -- a clinician's perspective

2022 · 3 Zit. · arXiv (Cornell University)

Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizability

2021 · 2 Zit. · arXiv (Cornell University)

Diagnostic accuracy of ChatGPT in dermatology: A meta-analysis of textual versus visual prompts

2025 · 0 Zit. · Journal of the American Academy of Dermatology