Digital medicine: Emergence, definition, scope, and future
Bibliographic record
Abstract
Shaoxiang Zhang, Ph.D., M.D., designed and founded the journal of Digital Medicine as editor-in chief. At Digital Medicine, Dr. Zhang's responsibilities include oversight of all editorial content and policies. His editorial background includes service as an editor-in-chief or associate editor or editorial board member for 15 academic journals including Clinical Anatomy, PLoS ONE, Chinese Journal of Regional Anatomy, Chinese Journal of Anatomy and Clinical Anatomy. A famous specialist in digital medicine and human anatomy, Dr. Zhang maintains an active research program. He is the principal investigator of the Chinese Visible Human Project, and more than 20 scientific projects else supported by National Science Foundation of China, including several key grant projects. He is a recipient of the National Science Fund for Distinguished Young Scholars of China, and the “National Excellent Talent”. Dr. Zhang has published more than 400 articles (over 60 are published in worldwide reputed SCI journals) and 21 books on topics such as human anatomy and digital medicine. His publications have received more than 2800 citations. In 2005, he was invited to deliver the keynote speech on the Chinese Visible Human Project at the 4 th Joint Meeting of the American Association of Clinical Anatomists and the British Association of Clinical Anatomists. He won the second prize of National Science and Technology Progress Award twice (in 2001 and 2007) for his contributions to the study of hand surgery and to the study of digital human dataset and its application, respectively. Dr. Zhang is the Distinguished Professor of digital medicine at the Institute of Digital Medicine and professor of human anatomy at the College of Basic Medicine of the Third Military Medical University. He took the lead to establish a digital-human-based anatomy teaching system and promote Digital Medicine to emerge as a new interdiscipline in China. Dr. Zhang has served as a leading scientist in numerous academic societies and committees, including the Chinese Society for Anatomical Sciences, Chinese Society of Digital Medicine, Discipline Appraisal Group of the Academic Degree Committee of the State Council, Expert Committee of Human Anatomy and Digital Anatomy in China, Chongqing Association of Digital Medicine and Chongqing Institute of Artificial Intelligence. Dr. Zhang received his medical degree from the Third Medical Military University. He had been the former Vice President of the Third Military Medical University (2006-2013). He has been the chairman of the Chinese Society for Anatomical Sciences since 2014 and the chairman of the Chinese Society of Digital Medicine since its foundation in 2011.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".