| Federated semi-supervised multi-task learning to detect COVID-19 and lungs segmentation marking using chest radiography images and Raspberry Pi devices: an internet of medical … MU Alam, R Rahmani Sensors 21 (15), 5025, 2021 | 23 | 2021 |
| Fedsepsis: A federated multi-modal deep learning-based internet of medical things application for early detection of sepsis from electronic health records using raspberry pi … MU Alam, R Rahmani Sensors 23 (2), 970, 2023 | 16 | 2023 |
| Exploring LRP and Grad-CAM visualization to interpret multi-label-multi-class pathology prediction using chest radiography MU Alam, JR Baldvinsson, Y Wang 2022 IEEE 35th international symposium on computer-based medical systems …, 2022 | 12 | 2022 |
| The accuracy of fully automated algorithms for surveillance of healthcare-associated urinary tract infections in hospitalized patients SD van der Werff, E Thiman, H Tanushi, JK Valik, A Henriksson, MU Alam, ... Journal of Hospital Infection 110, 139-147, 2021 | 9 | 2021 |
| Deep learning from heterogeneous sequences of sparse medical data for early prediction of sepsis MU Alam, A Henriksson, J Karlsson Valik, L Ward, N Pontus, H Dalianis 13th International Joint Conference on Biomedical Engineering Systems and …, 2020 | 6 | 2020 |
| Intelligent context-based healthcare metadata aggregator in internet of medical things platform MU Alam, R Rahmani Procedia Computer Science 175, 411-418, 2020 | 6 | 2020 |
| Cognitive Internet of Medical Things Architecture for Decision Support Tool to Detect Early Sepsis Using Deep Learning MU Alam, R R Communications in Computer and Information Science 1400, 366-384, 2021 | 3 | 2021 |
| Terminology Expansion with Prototype Embeddings: Extracting Symptoms of Urinary Tract Infection from Clinical Text. MU Alam, A Henriksson, H Tanushi, E Thiman, P Naucler, H Dalianis 14th International Joint Conference on Biomedical Engineering Systems and …, 2021 | 2 | 2021 |
| COVID-19 detection from thermal image and tabular medical data utilizing multi-modal machine learning MU Alam, J Hollmén, R Rahmani 2023 IEEE 36th International Symposium on Computer-Based Medical Systems …, 2023 | 1 | 2023 |
| (PhD Thesis) Advancing Clinical Decision Support Using Machine Learning & the Internet of Medical Things: Enhancing COVID-19 & Early Sepsis Detection MU Alam Department of Computer and Systems Sciences, Stockholm University, 2024 | | 2024 |
| SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction MU Alam, J Hollmén, JR Baldvinsson, R Rahmani Chianeh Nordic Machine Intelligence 3, 27-47, 2023 | | 2023 |
| (Master's Thesis) From speech to image; a novel approach to understand the hidden layer mechanisms of deep neural networks in automatic speech recognition MU Alam Institute for Natural Language Processing, University of Stuttgart, Germany, 2017 | | 2017 |
Rahim RahmaniProfessor in Computer Science at Stockholm UniversityVerified email at dsv.su.se
