Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril

Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study

Xiong, X., Hong, F., Xu, B., Wang, W., Zhou, M., Hu, P., Ren, Y., & Mao, Q. (2025) · Journal of Medical Internet Research · doi:10.2196/66612 · Cited by 10

Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health

Liaw, W. R., Westfall, J. M., Williamson, T. S., Jabbarpour, Y., & Bazemore, A. (2022) · JMIR Medical Informatics · doi:10.2196/27691 · Cited by 9

Artificial Intelligence and Machine Learning in Healthcare Sector

Chavda, V. P., Patel, K., Patel, S. H., & Apostolopoulos, V. (2023) · Wiley eBooks · doi:10.1002/9781119865728.ch13 · Cited by 11

Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity

(2023) · doi:10.1093/braincomms/fcae007 · Cited by 8

How to Design, Create, and Evaluate an Instruction-Tuning Dataset for Large Language Model Training in Health Care: Tutorial From a Clinical Perspective

Nazar, W., Nazar, G., Kamińska, A., & Daniłowicz‐Szymanowicz, L. (2025) · Journal of Medical Internet Research · doi:10.2196/70481 · Cited by 13

Assessing Clinicians’ Legal Concerns and the Need for a Regulatory Framework for AI in Healthcare: A Mixed-Methods Study

Alanazi, A. (2025) · Healthcare · doi:10.3390/healthcare13131487 · Cited by 11

Adoption of Machine Learning in US Hospital Electronic Health Record Systems: Retrospective Observational Study

Huang, H., Lyu, W., Hasan, M. M., & Houser, S. H. (2025) · Journal of Medical Internet Research · doi:10.2196/76126 · Cited by 12

A Perspective: Integrating Dental and Medical Research Improves Overall Health

Mouradian, W. E., Lee, J. C., Wilentz, J., & Somerman, M. J. (2021) · Frontiers in Dental Medicine · doi:10.3389/fdmed.2021.699575 · Cited by 9

Considerations for the implementation of machine learning into acute care settings

Bishara, A. M., Maze, E. H., & Maze, M. (2022) · British Medical Bulletin · doi:10.1093/bmb/ldac001 · Cited by 8

AI Approach Based on Deep Learning for Classification of White Blood Cells as a for e-Healthcare Solution

Monteiro, A. C. B., França, R. P., Arthur, R., & Iano, Y. (2021) · Springer eBooks · doi:10.1007/978-981-16-6542-4_18 · Cited by 8

Artificial Intelligence in Outpatient Primary Care: A Scoping Review on Applications, Challenges, and Future Directions

Iannone, S., Kaur, A., & Johnson, K. B. (2026) · Journal of General Internal Medicine · doi:10.1007/s11606-025-09938-0 · Cited by 8

Artificial intelligence in urology: Revolutionizing diagnostics and treatment planning

Eskandar, K. (2024) · Arab Journal of Urology · doi:10.1080/20905998.2024.2443334 · Cited by 10

Exploring Applications of Artificial Intelligence Tools in Clinical Care and Health Professions Education: An Online Module for Students

Agarwal, G. G., Ramamoorthi, L. S., Yuen, T., Merced, E., Brenner, J., Wu, W. Y., & Sabina, R. L. (2025) · MedEdPORTAL · doi:10.15766/mep_2374-8265.11524 · Cited by 13

Leveraging Clinical Decision Support and Integrated Medical-Dental Electronic Health Records to Implementing Precision in Oral Cancer Risk Assessment and Preventive Intervention

Rindal, D. B., & Mabry, P. L. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11090832 · Cited by 7

Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril. National Academy of Medicine. Una reseña

Rojas‐Gualdrón, D. F. (2022) · CES Medicina · doi:10.21615/cesmedicina.6571 · Cited by 7

Harnessing artificial intelligence for enhanced veterinary diagnostics: A look to quality assurance, Part II External validation

Pacholec, C., Flatland, B., Xie, H., & Zimmerman, K. (2025) · Veterinary Clinical Pathology · doi:10.1111/vcp.13407 · Cited by 7

Adaptation of the artificial ıntelligence literacy scale into Turkish: A cross-sectional application among healthcare workers, students, and children

Uluğ, E., Öner, K., ARSLANTAŞ, S., & Tatli, S. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13597-3 · Cited by 7

Optimal regimes for algorithm-assisted human decision-making

Stensrud, M. J., Laurendeau, J., & Sarvet, A. L. (2024) · Biometrika · doi:10.1093/biomet/asae016 · Cited by 8

A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts

Brandenburg, L. S., Schlager, S., Harzig, L. S., et al. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11092383 · Cited by 6

Computational Cartographic Recognition: Identifying Maps, Geographic Regions, and Projections from Images Using Machine Learning

Li, J., & Xiao, N. (2023) · Annals of the American Association of Geographers · doi:10.1080/24694452.2023.2166010 · Cited by 7

THE LEGAL CAPACITY (AL-AHLIYYAH) OF ARTIFICIAL INTELLIGENCE FROM AN ISLAMIC JURISPRUDENTIAL PERSPECTIVE

Sitiris, M., & Busari, S. A. (2024) · Malaysian Journal of Syariah and Law · doi:10.33102/mjsl.vol12no1.453 · Cited by 15

Teaching the bioethics of information technologies and artificial intelligence in healthcare: Case-based learning for identifying and addressing ethical issues

Barry, B. A., Sharp, R. R., & McGowan, M. L. (2025) · International Journal of Ethics Education · doi:10.1007/s40889-025-00218-3 · Cited by 10

Artificial intelligence in blood donor management: A narrative review

Badawi, M. A. (2025) · Vox Sanguinis · doi:10.1111/vox.70141 · Cited by 5

Artificial intelligence–driven transformation of healthcare systems: methods, applications, and future perspectives

Mishra, S. K., Hamadou, M., Gurung, K., Subba, A., Mukhia, P., Chhetri, T., Roy, A., Rai, P., & Georrge, J. J. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10617-4 · Cited by 6

Applications of Artificial Intelligence in Morocco’s Healthcare Sector: A Springboard to Medical Excellence

Idaomar, C., Idaomar, D., Hannaoui, M., & Chafik, K. (2024) · Journal of Computer and Communications · doi:10.4236/jcc.2024.129004 · Cited by 5

Artificial Intelligence in Outpatient Primary Care: A Scoping Review on Applications, Challenges, and Future DirectionsPreprint

Iannone, S., Kaur, A., & Johnson, K. B. (2025) · medRxiv · doi:10.1101/2025.05.12.25327223 · Cited by 5

Target product profiles for digital health technologies including those with artificial intelligence: a systematic review

Macdonald, T., Hogg, H. D. J., Dinnes, J., Verrinder, L., Maniatopoulos, G., Taylor‐Phillips, S., Shinkins, B., Dunbar, J. K., Solebo, A. L., Sutton, H., et al. (2025) · Frontiers in Health Services · doi:10.3389/frhs.2025.1537016 · Cited by 5

Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges

Zhang, Y., Zhang, X., Qi, X., Wu, X., Chen, F., Yang, G., & Fu, H. (2025) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2025.3619086 · Cited by 11

Artificial intelligence for sepsis management in the emergency department

de Vries, F. M. C., Wiersinga, W. J., & Schinkel, M. (2026) · BMC Infectious Diseases · doi:10.1186/s12879-026-12780-2 · Cited by 5

Artificial intelligence – the emperor's new clothes?

Hofmann, B. (2024) · Digital Health · doi:10.1177/20552076241287370 · Cited by 4

Catholic Health Care and AI Ethics: Algorithms for Human Flourishing

Miller, M. (2022) · The Linacre Quarterly · doi:10.1177/00243639221082226 · Cited by 4

Assessing acceptance of AI nurses for outpatients with chronic diseases: From nurses’ perspective

Uymaz, A. O., Uymaz, P., & Akgül, Y. (2024) · Environment and Social Psychology · doi:10.54517/esp.v9i5.2309 · Cited by 4

How to Induce Trust in Medical AI Systems

Reimer, U., Tödtli, B., & Maier, E. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-65847-2_1 · Cited by 4

Solving the Malady of Financial Toxicity Using Augmented Intelligence

Bhattacharyya, G. S., Bothra, S. J., Malhotra, H., et al. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00155 · Cited by 4

Research on the Application and Interpretability of Predictive Statistical Data Analysis Methods in Medicine

Nieminen, P. A. (2024) · BioMedInformatics · doi:10.3390/biomedinformatics4010018 · Cited by 4

Physicians’ perceptions and attitudes on artificial intelligence in hospital management: a qualitative study

Zhou, X., Jomhari, N., Farid, N. D. N., & Xing, Y. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-13815-1 · Cited by 4

A Secure and Interoperable Big Data Platform for AI-Driven Healthcare Solutions: Insights From the GATEKEEPER Project

Temporale, C., Salvo, E. D., Gaeta, E., et al. (2026) · IEEE Access · doi:10.1109/access.2026.3657440 · Cited by 3

Artificial Intelligence in Undergraduate Medical Education: A Cross-Sectional Study of Utilization Patterns and Perceptions Among Medical Students

Bokan, R. R., Malhotra, R., Vatsa, M., Bisht, K., Singla, M., & Choudhary, R. (2026) · Cureus · doi:10.7759/cureus.105503 · Cited by 4

Explainability in context: calibrating appropriate trust and reliance in artificial intelligence

Davis, S. E., & Salwei, M. E. (2026) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocag082 · Cited by 8

Operationalizing WHO Ethical Principles for Healthcare AI: A Lifecycle-Aligned Governance-by-Design Framework

Saraboji, K., Gopalakrishnan, K., Sood, D., Kaur, A., Shivaram, S., Helgeson, S. A., Arunachalam, S. P., & Mitra, D. (2026) · AI in Medicine · doi:10.3390/aimed1020016 · Cited by 4

Artificial Intelligence in Medical and Healthcare Service

Sangeetha, V., Mamatha, A., Vaneeta, M., et al. (2023) · Advances in healthcare information systems and administration book series · doi:10.4018/979-8-3693-0679-6.ch007 · Cited by 3

From diagnostic errors to diagnostic excellence in emergency care: Time to flip the script

Mahajan, P. (2024) · Academic Emergency Medicine · doi:10.1111/acem.15033 · Cited by 3

The Impact of the Latest Technology on Healthcare and how can it be leveraged to improve patient outcomes and reduce Healthcare costs

Wankhede, D. S., Mishra, V., Karnik, M. P., Kekane, A., & Shukla, A. (2023) · IEEE Global Conference for Advancement in Technology (GCAT) · doi:10.1109/gcat59970.2023.10353516 · Cited by 5

Metaverse for Enhancing Animal Welfare - Leveraging Sensor Technology and Ethical Considerations

Neethirajan, S. R. (2024) · Journal of Emerging Computer Technologies · doi:10.57020/ject.1460995 · Cited by 3

Transparent Communications for Human–Machine Teaming

Chen, J. Y. C. (2023) · doi:10.1002/9781119863663.ch10 · Cited by 4

AI-Powered Human Resource Management: Redefining the Future of Work and Workforce

Agrawal, V., Taluja, A., Sharma, S., et al. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-5535-9_5 · Cited by 2

Building a methodological profile for communication’s study of the passive generation of information

Rasheed, H., & Holbert, R. L. (2025) · Communication and Change · doi:10.1007/s44382-025-00020-1 · Cited by 2

Artificial Intelligence in Allergic Diseases Prediction and Management

Guo, D., Xiao, N., Chen, L., & Zhang, S. (2026) · Current Treatment Options in Allergy · doi:10.1007/s40521-026-00413-7 · Cited by 2

MEDS — An Emerging Data Standard and Ecosystem for Health AI Research

McDermott, M. B. A., Steinberg, E., Fries, J., van de Water, R. P., Pang, C., Rockenschaub, P., Renc, P., Oh, J. H., Stankevičiūtė, K., Xu, J., et al. (2026) · NEJM AI · doi:10.1056/aira2501253 · Cited by 3

Ethics of Autonomous AI Clinical Trials: Delphi Study

Nichol, A. A., Youssef, A., Larson, D. B., Abràmoff, M. D., Wolf, R. M., Char, D. S., & Martinez‐Martin, N. (2026) · Journal of Medical Internet Research · doi:10.2196/91472 · Cited by 1

Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

Lourida, K. G., & Louridas, G. E. (2022) · Cardiogenetics · doi:10.3390/cardiogenetics12020015 · Cited by 2

Agent Transparency for Human-Autonomy Teaming

Chen, J. Y. C., & Barnes, M. J. (2022) · Automation, collaboration, and e-services · doi:10.1007/978-3-031-10788-7_15 · Cited by 3

Recommender Diagnosis System with Fuzzy Logic in Cloud Environment

Aboghazalah, M. M., Elnemr, R., Elsayed, N., El‐Sayed, A., & Elkafrawy, P. (2022) · International Conference on Language Engineering (ESOLEC) · doi:10.1109/esolec54569.2022.10009214 · Cited by 2

The Impact of Digital Transformation in HealthCare

Băjenaru, L., & Dobre, C. (2024) · Intelligent systems reference library · doi:10.1007/978-3-031-63337-9_3 · Cited by 3

Brief Introduction to Artificial Intelligence and Machine Learning

Motamedian, S. R., Hassanzadeh-Samani, S., Nadimi, M., Shobeiri, P., Motie, P., Rohban, M. H., Mahmoudinia, E., & Mohammad‐Rahimi, H. (2023) · Springer eBooks · doi:10.1007/978-981-19-8602-4_14 · Cited by 4

Yemeni university students public perceptions toward the use of artificial intelligence in healthcare: A cross-sectional studyPreprint

Hatem, N. A. H., Ibrahim, M. I. M., & Yousuf, S. A. (2024) · medRxiv · doi:10.1101/2024.02.27.24303457 · Cited by 2

Increasing the Patient-Centeredness of Predictive Analytics Tools

Crossnohere, N. L., Childerhose, J. E., & Bose‐Brill, S. (2022) · Patient · doi:10.1007/s40271-022-00595-7 · Cited by 1

Promises and Perils of Artificial Intelligence in Surgery: The Critical Pathways for Successful Healthcare Outcomes

Kim, Y., Melzer, A., Kim, S., & Barach, P. R. (2024) · Springer eBooks · doi:10.1007/978-3-031-68574-3_8 · Cited by 1

The Problem of Ethics in Artificial Intelligence for Healthcare

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0002 · Cited by 1

Artificial Intelligence Applications in Obstetrics and Gynaecology

Vedula, S. S., & Chen, C. C. G. (2025) · Journal of Obstetrics and Gynaecology Canada · doi:10.1016/j.jogc.2025.103067 · Cited by 1

Role of Artificial Intelligence in Health Research: Opportunities, Challenges, and Implications for Medical Education

Deonandan, R. (2026) · Cureus · doi:10.7759/cureus.106579 · Cited by 1

Integrating Preventive Healthcare for Lifelong Well-Being: Policy Strategies and Practical Approaches

Koutentakis, M., & Postula, M. (2026) · Healthy ageing and longevity · doi:10.1007/978-3-032-20006-8_3 · Cited by 2

Analysis of approaches to determining legal liability for the actions of artificial intelligence in the medical field: the experience of the United States and Russia.

Atabekov, A. R. (2023) · Юридические исследования · doi:10.25136/2409-7136.2023.6.40928 · Cited by 1

THE IMPACT OF THE INTRODUCTION OF ARTIFICIAL INTELLIGENCE TECHNOLOGIES ON THE CURRENT HUMAN RIGHTS AND FREEDOMS CONCEPT

Пашков, В., Harkusha, A. O., & Soloviov, O. (2023) · Polski Merkuriusz Lekarski · doi:10.36740/merkur202306111 · Cited by 1

Künstliche Intelligenz in der Kopf-Hals-Chirurgie: Potenziale und ethische Überlegungen

Fiedler, L. S., Meyer, T., & Hüttemann, S. (2024) · Laryngo-Rhino-Otologie · doi:10.1055/a-2369-0263 · Cited by 1

Artificial Intelligence in Biomarker Discovery and Disease Diagnosis-2

Shah, S. N. A., & Parveen, R. (2025) · Springer eBooks · doi:10.1007/978-981-96-8176-1_7 · Cited by 1

Prevention Trials: Challenges in Design, Analysis, and Interpretation of Prevention Trials

Jiang, S., & Colditz, G. A. (2022) · Springer eBooks · doi:10.1007/978-3-319-52636-2_96 · Cited by 2

Human-Centered Design of an Artificial Intelligence (AI) Monitoring System: The Vanderbilt Algorithmovigilance Monitoring and Operations System (VAMOS)Preprint

Salwei, M. E., Davis, S. E., Reale, C., Novak, L. L., Walsh, C. G., Beebe, R., Nelson, S., Sundrani, S. C., Rose, S. L., Wright, A. T., et al. (2025) · medRxiv · doi:10.1101/2025.06.05.25329034 · Cited by 1

Prevention Trials: Challenges in Design, Analysis, and Interpretation of Prevention Trials

Jiang, S., & Colditz, G. A. (2021) · Springer eBooks · doi:10.1007/978-3-319-52677-5_96-1

The Way Forward

Baernholdt, M., & Boyle, D. K. (2021) · Springer eBooks · doi:10.1007/978-3-030-69063-2_15

5G, Big Data, and AI for Smart City and Prevention of Virus Infection

Ren, S., & Shen, B. (2022) · Advances in experimental medicine and biology · doi:10.1007/978-981-16-8969-7_9

The Pharmacist’s View: Patient-Centered Care Through the Lens of a Pharmacist

Franky, F., & Fung, B. K. (2022) · Health informatics · doi:10.1007/978-3-030-91237-6_6

Data Analytics, Artificial Intelligence and Data Visualization

Ozkaynak, M., & Skiba, D. J. (2022) · Health informatics · doi:10.1007/978-3-030-91237-6_19

La evaluación de tecnologías en salud basadas en inteligencia artificial ¿debería ser diferente?

Rojas‐Gualdrón, D. F. (2022) · Revista CES Salud Pública y Epidemiología · doi:10.21615/cesspe.6572

AI and Medical Education

Greenhill, A. T. (2023) · AI in Clinical Medicine · doi:10.1002/9781119790686.ch3

What Will It Take to Make Healthcare Safer?

Bates, D. W., Folcarellli, P., & Mort, E. A. (2023) · Journal of Healthcare Management Standards · doi:10.4018/jhms.329200

“Health Is the Real Wealth”: Unsupervised Approach to Improve Explainability in Health-Based Recommendation Systems

Ortiz-Viso, B., Fernandez‐Basso, C., Gómez-Sánchez, J., & Martín-Bautista, M. J. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-42935-4_19

Prophecy and promise: Sociotechnical imaginaries in academic medicine strategic planningPreprint

Rowland, P., Brydges, M., & Kulasegaram, K. M. (2023) · Research Square · doi:10.21203/rs.3.rs-3697943/v1

Assessing and Addressing Model Trustworthiness Trade-offs in Trauma Triage

Talbert, D. A., Phillips, K., Brown, K. E., & Talbert, S. (2024) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213024600078

Industry 4.0 applications and maintenance in the medical field

Dogra, R., Dubey, A., & Taneja, S. (2024) · AIP conference proceedings · doi:10.1063/5.0221520

Study on Reliability in Healthcare Training and Critical Evaluation of ChatGPT AI Performance: Simulation of the Admission Test for the Hospital Pharmacy Specialization School in Turin, Italy

Castellana, E. (2024) · Hospital Pharmacy · doi:10.1177/00185787241299039

Developing Tools and Assessments to Evaluate Healthcare Professionals' AI Competencies

Torres-Zambrano, G. M. (2024) · Advances in medical technologies and clinical practice book series · doi:10.4018/979-8-3693-4422-4.ch005

Innovations in Healthcare Management: Balancing Cost, Quality, and Access

Bhardwaj, U., Mane, M., & Samal, S. (2022) · Health Leadership and Quality of Life · doi:10.56294/hl2022100

Algoritmo de Inteligência Artificial para Detecção Precoce de Patógenos em Amostras Clínicas

Chaves, A. N. D. S. (2025) · Saúde Coletiva (Barueri) · doi:10.36489/saudecoletiva.2025v15i94p15283-15294 · Cited by 11

The Future of AI in Claims Adjudication and Health Insurance: Transforming Operations Through Intelligent Automation

Bag, U. (2025) · International Journal of Advanced Research in Science, Communication and Technology · doi:10.48175/ijarsct-24653 · Cited by 1

Transformación de la Administración y gestión sanitaria mediante un ecosistema basado en inteligencia artificial

Chimenea, Á. (2025) · Instituto Andaluz de Administración Pública eBooks · doi:10.46735/iaap-pub.246

Ethical Smart Care

Hine, C. (2025) · doi:10.1093/9780197764527.001.0001

Designing Ethics into Infrastructures

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0004

Care Ethics and Smart Care

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0005

List of Tables and Figures

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.002.0005

Introducing Smart Care, Dementia, and Care Ethics

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0001

Conclusion

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0007

Dedication

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.002.0004

Infrastructural Ethics of Smart Care

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0003

Lived Experience of Smart Care

Hine, C. (2025) · Oxford University Press eBooks · doi:10.1093/9780197764527.003.0006

The future of narcolepsy treatment: what role will artificial intelligence play?

Maghsoudi, A., Ramezani, A., Razjouyan, J., & Sharafkhaneh, A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-30004-2.00050-x

AI-Powered Triage of Suicidal Ideation in Adolescents: A Comparative Evaluation of Large Language Models Using Synthetic Clinical VignettesPreprint

Mansoor, M. A. (2025) · medRxiv · doi:10.1101/2025.08.05.25333046 · Cited by 2

AI-Powered Triage of Suicidal Ideation in Adolescents: A Comparative Evaluation of Large Language Models Using Synthetic Clinical Vignettes (Preprint)Preprint

Mansoor, M. A. (2025) · doi:10.2196/preprints.82288

AI Meets Digital Public Health

Steinert, L., Diethei, D., Hoel, V., Hahn, H. K., Wolf‐Ostermann, K., Wright, M. N., & Schultz, T. (2025) · Springer series on epidemiology and public health · doi:10.1007/978-3-031-90154-6_27

Navigating Barriers: Disability, Healthcare Information Seeking, and AI ‐Enabled Chatbots

Gray, M., & Threats, M. (2025) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1433

Susquehanna Chorale Spring Concert "Roots and Wings"

Hawkins, D. (2017)

Using DataGrid Control to Realize DataBase of Querying in VB6.0

Hu, S. (2000) · Modern Computer

Study and Two Types of Typical Usage of DataGrid Web Server Control

Hai-tao, L. (2005) · Modern Computer

Achieving Parameter of DBSCAN Based on Datagrid

Xu, Q. (2010)

PACWON: A parallelizing compiler for workstations on a network

Das, D. K., & Das, P. P. (1998) · Journal of Systems Architecture · doi:10.1016/s1383-7621(97)00078-7