Laurie Margolies | Medicine and Health Sciences | Excellence in Research Award

Dr. Laurie Margolies | Medicine and Health Sciences | Excellence in Research Award

Dr. Laurie Margolies | Medicine and Health Sciences | MD at Icahn School of Medicine at Mount Sinai | United States

Dr. Laurie Margolies is a distinguished academic physician and internationally recognized expert in breast imaging and diagnostic radiology, known for her leadership in integrating advanced imaging technologies and artificial intelligence into clinical cancer care. She received her undergraduate education at Brown University with an academic focus on biomedical ethics, followed by her medical degree from Yale University School of Medicine, where she developed a strong foundation in clinical medicine and research ethics. Dr. Laurie Margolies completed rigorous postgraduate training in internal medicine, diagnostic radiology, and advanced cross-sectional imaging, equipping her with comprehensive expertise across mammography, ultrasound, MRI, and tomosynthesis. Professionally, Dr. Laurie Margolies has held progressive academic appointments culminating in a full professorship in diagnostic, molecular, and interventional radiology at a leading academic medical center, while simultaneously serving in senior health-system leadership roles including Vice Chair and System Chief for Breast Imaging.

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Citations2177

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🟦 CitationsΒ  Β  πŸŸ₯ DocumentsΒ  Β  🟩 h-index


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Featured Publications

Performance of an Artificial Intelligence Support System on Screening Mammography Cases Proceeding to Stereotactic Biopsy
– Cancers (Open Access)
The Tyrer-Cuzick Risk Model: Is It Effective for All Races?
– Clinical Imaging
Patient Perception of Artificial Intelligence in Breast Imaging: A Pilot Survey Study
– Clinical Imaging
Suspicion for Sarcoma: Clinical Presentation, Multi-Modality Imaging Evaluation, and Ultrasound Artificial Intelligence-Based Decision Support
– Cancers (Open Access)
Breast Lymphoma: Imaging Features, Clinical Presentation, and Ultrasound Artificial Intelligence Decision Support
– Clinical Imaging
Artificial Intelligence for Assessment of Digital Mammography Positioning Reveals Persistent Challenges
– Journal of Breast Imaging
Breast Arterial Calcifications on Mammography: A Review of the Literature
– Review Article
Identifying Frequently Endorsed Benefits and Barriers to Breast Cancer Screening for African-Born Women in the NYC Metropolitan Area: A Pilot Study
– Journal of Racial and Ethnic Health Disparities
Low-Dose Chest CT: Participating in the Rise of Breast Density Awareness
– Journal of Women’s Health

Wei Liu | Medicine and Health Sciences | Best Researcher Award

Wei Liu | Medicine and Health Sciences | Best Researcher Award

Prof. Dr Wei Liu Hunan, University of Chinese Medicine, China

Prof. Dr. Wei Liu is a distinguished scholar in Artificial Intelligence πŸ€–, Medical Informatics πŸ₯, and Intelligent Software Engineering πŸ’», serving as Deputy Dean at Hunan University of Chinese Medicine. With a Ph.D. in Engineering πŸŽ“, he has made groundbreaking contributions through 100+ research papers πŸ“„ (30+ indexed in SCI/EI), 2 monographs πŸ“š, and 9 textbooks πŸ“–. His 30+ software copyrights πŸ’‘ and leadership in 20+ major projects πŸš€, including collaborations with Huawei and national research foundations, solidify his expertise. As a Young Backbone Teacher of Hunan Province, he also excels in mentoring, guiding students to 300+ awards πŸ…, including 10+ national gold prizes πŸ†. His teaching innovation has earned him national and provincial-level honors, while his contributions to Traditional Chinese Medicine (TCM) Informatics 🌿 further highlight his multidisciplinary excellence. Recognized as a National Certified System Architect πŸ—οΈ, SCI journal reviewer 🧐, and a member of CCF, ACM, and CAIS, Prof. Liu is a true leader in his field.

Publication Profile

Scopus

Education

Prof. Dr. Wei Liu holds a Ph.D. in Engineering (Computer Application Technology) πŸ–₯️ from a prestigious institution, where he specialized in Artificial Intelligence πŸ€– and Medical Informatics πŸ₯. His doctoral research focused on intelligent software systems, integrating machine learning πŸ“Š with healthcare applications 🏩. Prior to his Ph.D., he completed his Master’s degree πŸŽ“ in Computer Science, gaining deep expertise in data-driven decision-making πŸ’Ύ and intelligent algorithms πŸ”. His academic journey also includes undergraduate studies in Software Engineering πŸ’‘, where he built a strong foundation in computational intelligence 🧠, biomedical computing πŸ₯, and software development πŸ’». With an interdisciplinary education spanning engineering, computer science, and informatics, Prof. Liu combines technical depth with practical innovation, making his academic background perfectly suited for pioneering AI-driven healthcare solutions πŸš‘. His commitment to education πŸ“š continues as he mentors students and professionals in next-generation AI research and applications πŸ€–πŸ“Š.

Experience

Prof. Dr. Wei Liu serves as the Deputy Dean of the School of Informatics πŸ›οΈ at Hunan University of Chinese Medicine, leading research in Artificial Intelligence πŸ€–, Medical Informatics πŸ₯, and Software Engineering πŸ’». As a Professor and Senior Engineer πŸ‘¨β€πŸ”¬, he supervises Master’s students πŸŽ“, guiding them in cutting-edge AI research πŸš€. With a rich teaching career πŸ“š, he has developed three top-level provincial courses πŸŽ–οΈ and ranked 1st in the Hunan Provincial Teaching Competition πŸ†. His industry collaborations with Huawei and leadership in 20+ national projects πŸ—οΈ highlight his practical impact 🌍. He actively contributes as a Vice President of the Hunan Association for TCM Informatics 🌿 and serves on multiple national AI and computing committees 🀝. His work as an SCI journal reviewer 🧐 and National Certified System Architect πŸ—οΈ ensures that his research, teaching, and innovation continue to shape the future of AI-driven medical solutions πŸ”¬.

Awards & Honors

Prof. Dr. Wei Liu is a distinguished researcher and educator 🌟, renowned for his contributions to AI, medical informatics, and teaching innovation πŸ“š. His accolades include the National Teaching Innovation Competition Second Prize πŸ† (2024), 1st Place in the Hunan Provincial Teaching Competition πŸŽ–οΈ, and the National TCM Informatics Teaching Gold Prize πŸ…. He has been honored as the β€œMost Knowledgeable Young Teacher” in Hunan Province πŸ† and recognized as a Young Backbone Teacher πŸ‘¨β€πŸ«. A recipient of the Huawei Industry-Academia Collaboration Excellence Award πŸ…, he also serves as an Executive Member of National AI Committees πŸ€–. His mentorship has led students to win 300+ awards πŸ†, including over 10 national gold prizes πŸ₯‡. As a pioneer in AI-driven medical technologies 🌍, his impact extends across academia and industry πŸš€.

Research Focus

Prof. Dr. Wei Liu’s research spans Artificial Intelligence πŸ€–, Medical Informatics πŸ₯, and Intelligent Software Engineering πŸ’», focusing on AI-driven healthcare solutions πŸ“Š, big data analysis 🏩, and intelligent diagnosis πŸ₯. His expertise includes AI-based disease prediction, NLP for medical data πŸ“œ, deep learning for medical imaging πŸ§ πŸ“Έ, and IoT-driven smart healthcare πŸš‘. Integrating AI with Traditional Chinese Medicine πŸŒΏπŸ€–, he pioneers innovative patient care solutions. With 30+ software copyrights πŸ’‘, 100+ high-impact publications πŸ“„, and national-level projectsβ€”including Huawei collaborations πŸš€β€”his work enhances precision medicine, diagnostics, and medical software applications 🌍, revolutionizing healthcare technology.

Publication Top Notes

Recognition of Hand-Drawn Hydrocarbon Structure Formulas Using Anchor-Free Detector

Classification of cold and hot medicinal properties of Chinese herbal medicines based on graph convolutional network

ChemReco: automated recognition of hand-drawn carbon–hydrogen–oxygen structures using deep learning

SQCS: A sustainable quality control system for spatial crowdsourcing via three-party evolutionary game: Theory and practice

Truth based three-tier Combinatorial Multi-Armed Bandit ecosystems for mobile crowdsensing

YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications