Items where Author is "Khalid, SG"
Journal article
HOUKAN, A., SAHOO, A.K., GOCHHAYAT, S.P., SAHOO, P.K., LIU, H., KHALID, S.G. and JAIN, P., 2024. Enhancing security in industrial IoT networks: machine learning solutions for feature selection and reduction. IEEE Access, 12, pp. 160864-160883. ISSN 2169-3536
KANWAL, K., ASIF, M., KHALID, S.G., LIU, H., QURASHI, A.G. and ABDULLAH, S., 2024. Current diagnostic techniques for pneumonia: a scoping review. Sensors, 24 (13): 4291. ISSN 1424-8220
KANWAL, K., KHALID, S.G., ASIF, M., ZAFAR, F. and QURASHI, A.G., 2024. Diagnosis of community-acquired pneumonia in children using photoplethysmography and machine learning-based classifier. Biomedical Signal Processing and Control, 87 (Part A): 105367. ISSN 1746-8094
KANWAL, K., ASIF, M., KHALID, S.G., WASI, S., ZAFAR, F., KIRAN, I. and ABDULLAH, S., 2023. Comparative analysis of photoplethysmography signal quality from right and left index fingers. Traitement du Signal, 40 (5), pp. 2199-2214. ISSN 0765-0019
MEHMOOD ALI, S., KHALID, S.G., ALI, U. and HAMEED, K., 2023. A blueprint design of optical-based wristband for non-invasive and continuous health status monitoring of sickle cell disease patients. Journal of Applied Research and Technology, 21 (1), pp. 133-144. ISSN 1665-6423
KHALID, S.G., ALI, S.M., LIU, H., QURASHI, A.G. and ALI, U., 2022. Photoplethysmography temporal marker-based machine learning classifier for anesthesia drug detection. Medical and Biological Engineering and Computing, 60 (11), pp. 3057-3068. ISSN 0140-0118
Chapter in book
ZHANG, W., KHALID, S.G., SADIQ, S., LIU, H. and WONG, J.Y.H., 2024. Chapter 1 - a systematic review on intelligent diagnosis of diabetes using rule-based machine learning techniques. In: S. DASH, S.K. PANI, W. SUSILO, B.M.Y. CHEUNG and G. TSE, eds., Internet of things and machine learning for type I and type II diabetes: use cases. London: Elsevier, pp. 3-16. ISBN 9780323956864
WU, W., ZHANG, W., SADIQ, S., TSE, G., KHALID, S.G., FAN, Y. and LIU, H., 2024. Chapter 27 - an up-to-date systematic review on machine learning approaches for predicting treatment response in diabetes. In: S. DASH, S.K. PANI, W. SUSILO, B.M.Y. CHEUNG and G. TSE, eds., Internet of things and machine learning for type I and type II diabetes: use cases. London: Elsevier, pp. 397-409. ISBN 9780323956864