Ausgewählte Publikationen
Under Preperation:
33. Lu, H., Ghadban Y., Adavi U., Gara, S., Ankita Sharma, A., John, R., Praveen D., Hirst, J., ‘RiLLM: Reasoning-informed LLM Distillation for Responsible AI in Healthcare: a Teacher-Student Few-shot learning framework on AI foundation models for frontline healthcare communications’, in preparation.
32. Lu, H., Hirst, J., Lu, P., Mackillop, L., Clifton, D., ‘Federated Multiple-Hospital Patient Monitoring for Gestational Diabetes in Pregnancy’, in preparation.
31. Lu, H., Ceritli, Hirst, J., T., Mackillop, L., Clifton, D., ‘Gestational Diabetes Phenotype Discoveries’, in preparation.
Under Review:
30. In-Network Machine Learning on IoMT Edge Gateways, submitted to ACM/IEEE Sensys 2026.
29. Development and Clinical Validation of SMARThealth GPT: An Artificial Intelligence Chatbot for Women’s Health and Community Health Workers in India, submitted to Scientific Reports
28. Federated Learning for Healthcare Virtual Wards using Edge Computing: A Survey, submitted to ACM Computing Survey.
27. Governance of Medical Devices Augmented with Large Language Models, submitted to BMC Global and Public Health.
2025
26. Majumdar, S., Das, N., Sharma, A., Ghadban, Y., Adavi, U., Gara, S., Lu, H., John, R., Kumar, B., Devarsetty, P., Hirst J., 'SMARThealth Pregnancy (SHP) GPT: Addressing Gender Bias in LLM for Community Health Workers in Rural India', International Conference on Gender and Technology Conference, 2025.
25. Zou, Q., Pei, Y., Yang, B., Yuan, W., Lu, H., 'An Adaptive Monitoring Method for SMA Wires by Integrating Dual Resistance Signals and Machine Learning', Mechanical Systems and Signal Processing, Volume 235, 112954.
24. Ghadban, Y., Astbury, N., Kurdi, A., Sharma, A., Ope, B., Liu, T. Y., MacKillop, L., Lu, H., and Hirst, J. , 'Prediction models of gestational diabetes short-and longer-term outcomes: A systematic review', Obesity Reviews(2025): e13934.
23. Chauhan, V. K., Clifton, L., Salaün, A., Lu, H. Y., Branson, K., Schwab, P., Nigam, G., Clifton, D. A. 'Sample Selection Bias in Machine Learning for Healthcare', in press, ACM Transactions on Computing for Healthcare, 2025.
22. Xin, Q. Y., Pei, Y. C., Lu, H. Y., Huang, Y. H., Liu, J. Y., Chatwin, C., 'Advanced unconditional signal processing model for cross-section contour reconstruction using multi-channel measurements', Applied Mathematical Modelling, 138, 115762.
21. Zou, Q., Pei, Y. C., Wang, H. P., Xu, J., Lu, H. ,'A resistance-only approach for shape memory alloy wire adaptive monitoring with auxiliary winding temperature-sensing wire', Mechanical Systems and Signal Processing, 225, 112280.
2024
21. L. Liu, H. Lu, M. Whelan, Y. Chen and X. Ding, "CiGNN: A Causality-Informed and Graph Neural Network Based Framework for Cuffless Continuous Blood Pressure Estimation," in IEEE Journal of Biomedical and Health Informatics, vol. 28, no. 5, pp. 2674-2686, 2024, doi: 10.1109/JBHI.2024.3377128.
20. Xin, Q. Y., Pei, Y. C., Wang, B., Zhang, B., Qu, C., Lu, H., Digital synchronous measurement method for two-dimensional in-plane displacement using check-code. Measurement, 225:114047, 2024.
19. Pei, Y. C., Wang, X. Y., Yao, Z. Y., Wang, B. H., Liao, Z. H., Lu, H. , 'The driving characteristics of bidirectional SMA wire actuators-Theoretical modeling and experimental testing', Sensors and Actuators A: Physical, 372, 115328.
2023
18. Ghadban Y., Lu, H, Adavi U., Gara, S., Ankita Sharma, A., John, R., Praveen D., Hirst, J., ‘Transforming Healthcare Education: Harnessing Large Language Models for Frontline Worker Capacity Building using retrieval-augmented generation’, accepted, NeurIPs workshop in LLM for Education, 2023.
17. Lu, H., Lu, P., Hirst, J.E., Mackillop, L., Clifton, D.A. ‘A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus’, Sensors, 23:7990. doi:10.3390/s23187990
16. Lu, H., Ding, X., Hirst J., Yang, Y., Yang, J., Mackillop L., Clifton, D., ‘Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes’, IEEE Review of Biomedical Engineering, 2023.
15. Hirst, J., Lu, H., Mackillop, L., Ghadban., Y., Saravanan, P., White, W., Complex clinical data and Gestational Diabetes Mellitus, National Centre for Research Methods, 05/2023. https://eprints.ncrm.ac.uk/id/eprint/4930/1/Complex%20clinical%20data%20and%20Gestational%20Diabetes%20Mellitus.pdf
14. Lu, P., Creagh, A.P., Lu, H.Y., Hai, H.B., VITAL Consortium; Thwaites, L., Clifton, D.A., ‘2D-WinSpatt-Net: A Dual Spatial Self-Attention Vision Transformer Boosts Classification of Tetanus Severity for Patients Wearing ECG Sensors in Low- and Middle-Income Countries’, Sensors, 23, 7705. doi:10.3390/s23187705
13. Talyor, L., Ding, X., Clifton, D., Lu, H., ‘Wearable vital signs monitoring for patients with asthma: a review,’ IEEE Sensors Journal, 02/2023. Available online at: https://ieeexplore.ieee.org/abstract/document/9967964
12. Xin, Q. -Y., Pei, Y. -C., Lu, H., Clifton, D., Wang, B., Chuan, Q., Luo, M. -Y., ‘A distribution-based selective optimization method for eliminating periodic defects in harmonic signals,’ Mechanical Systems and Signal Processing, 185, 2023. Available online at: https://doi.org/10.1016/j.ymssp.2022.109781
2022
11. Lu H., ‘MedMetrics: biometrics passports in medical and clinical healthcare that enable AI and Blockchain’, Recent Advances in Biometrics, pp 115-129, ISBN: 1803554568, IntechOpen, 2022. Available online at: https://www.intechopen.com/chapters/81969
10. Yang, J., Clifton, D., Hirst, J., Mackillop, L., Lu, H., ‘Machine Learning-Based Risk Stratification for Gestational Diabetes Management’, Sensors, 22 (13), 4805, 2022. Available online at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9268930/
9. Lu, H., Hirst, J., Yang, J., Mackillop, L., Clifton, D., ‘Standardising the assessment of caesarean birth using an Oxford caesarean prediction score for mothers with gestational diabetes’, Healthcare Technology Letters 9 (1-2), 1-8, 2022. Available online at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8928011/
8. Sui, W., Pei Y., Wang, b., Wu, J., Wang, D., Wang, B., Wang, L., Lu, H., ‘Quantitative Self-Sensing Energy Storage and Ejection Release by Superelastic Shape Memory Alloy Wire’, Mechanical Engineering and Signal Processing, 2022. doi:10.1016/j.ymssp.2022.110045
7. Pei, Y., Wu, J., Wang, B., Wang, C., Guan, J., Lu, H., ‘A Machine Learning Empowered Shape Memory Alloy Gripper with Self-sensing of Displacement-Force-Stiffness’, IEEE Transactions on Industrial Electronics, 2022. doi:10.1109/tie.2022.3222655
2021
6. Kerdegari, H., Phung, N. T. H., McBride, A., Pisani, L., Nguyen, H. V., Duong, T. B., Vietnam ICU Translational Applications Laboratory Investigators, Gomez, A. 'B-line detection and localization in lung ultrasound videos using spatiotemporal attention'. Applied Sciences, 11(24). doi:10.3390/app112411697
5. Van, H., Hao, N., Phan Nguyen Quoc, K., Hai, H., Khoa, L., Yen, L., Vietnam ICU Translational Applications Laboratory Investigators, Thwaites, G. 'Vital sign monitoring using wearable devices in a Vietnamese intensive care unit', BMJ Innovations, 7 (Supplement 1), S7-S11. doi:10.1136/bmjinnov-2021-000707
4. DECOVID Investigators, et al, ‘DECOVID, a UK two-centre harmonized database of acute care electronic health records for COVID-19 research’, to be submitted to a selected journal by the Alan Turing Institute.
3. DECOVID Investigators, et al, ‘Empirical comparison of NEWS-2 and supervised learning methods to predict deterioration for COVID-19 patients’, to be submitted to a selected journal by the Alan Turing Institute.
2020
2. Bird, K., Chan, G., Lu, H., Greeff H., Allen J., Abbott D., Menon C., Lovell, N.H., Chan, W., Fletcher, R.R., Alian, A., Ward, R., Elgendi, M., ‘Assessment of Hypertension Using Electrocardiogram Features: A Review’, Frontiers in medicine 7, 583331, 2020. doi:10.3389/fmed.2020.583331
2015-2019 Career Break
1. Little, R., Jamin, Y., Boult, J. K. R., Watson, Y., Cheung, S., Holliday, K., Lu, H., Mchugh, D., Irlam, J., Betts, G., Ashton, G., Reynolds, A. R., Maddineni, S., Clarke, N. W, Waterton, J., Robinson, S. P. , ‘Combined Oxygen and Gadolinium Enhanced MR Imaging of Hypoxia in Renal Carcinoma: Comparison with Susceptibility MR Imaging and Pathology’, 2017:12, Radiology. doi:10.1148/radiol.2018171531