A5002586041- Artificial Intelligence in Healthcare and Education
- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- Radiation Dose and Imaging
- Advanced Radiotherapy Techniques
- Sports injuries and prevention
- Meta-analysis and systematic reviews
- Cardiovascular and exercise physiology
- Health Systems, Economic Evaluations, Quality of Life
- Sports Performance and Training
University of Washington
2023-2025
American Association of Physicists in Medicine
2023
Yale New Haven Hospital
2022
Rapid advances in artificial intelligence (AI) and machine learning, specifically deep learning (DL) techniques, have enabled broad application of these methods health care. The promise the DL approach has spurred further interest computer-aided diagnosis (CAD) development applications using both "traditional" newer DL-based methods. We use term CAD-AI to refer this expanded clinical decision support environment that uses traditional AI Numerous studies been published date on tools for...
Abstract The adoption of artificial intelligence (AI) tools in medicine poses challenges to existing clinical workflows. This commentary discusses the necessity context-specific quality assurance (QA), emphasizing need for robust QA measures with control (QC) procedures that encompass (1) acceptance testing (AT) before use, (2) continuous QC monitoring, and (3) adequate user training. discussion also covers essential components AT QA, illustrated real-world examples. We highlight what we see...
Abstract Background Accurately determining the Peak Skin Dose (PSD) delivered to patient during Fluoroscopically Guided Interventional Procedures (FGIP) is crucial for assessing potential radiation‐induced skin injuries and necessary follow‐up care exposed patients. Purpose This study evaluates accuracy of PSD estimation model FGIPs using mathematical anthropomorphic computational phantoms that mimic dimensions imaged provides their description. Methods The modeling FGIP calculation peak...
Abstract Background Measurement of Computed Tomography (CT) beam width is required by accrediting and regulating bodies for routine physics evaluations due to its direct correlation patient dose. Current methods performing CT measurement require special hardware, software, and/or consumable films. Today, most 100‐mm pencil chambers with a digital interface used evaluate Dose Index (CTDI vol ) have sufficiently high sampling rate reconstruct high‐resolution dose profile any acquisition mode....