Mahbub Ul Alam

According to our database, Mahbub Ul Alam authored at least 9 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

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 and Jetson Nano Devices.

Mahbub Ul Alam, Rahim Rahmani

Sensors, January, 2023

SHAMSUL: Simultaneous Heatmap-Analysis to investigate Medical Significance Utilizing Local interpretability methods.

Mahbub Ul Alam, Jaakko Hollmén, Jón Rúnar Baldvinsson, Rahim Rahmani

CoRR, 2023

COVID-19 detection from thermal image and tabular medical data utilizing multi-modal machine learning.

Mahbub Ul Alam, Jaakko Hollmén, Rahim Rahmani

Proceedings of the 36th IEEE International Symposium on Computer-Based Medical Systems, 2023

2022

Exploring LRP and Grad-CAM visualization to interpret multi-label-multi-class pathology prediction using chest radiography.

Mahbub Ul Alam, Jón Rúnar Baldvinsson, Yuxia Wang

Proceedings of the 35th IEEE International Symposium on Computer-Based Medical Systems, 2022

2021

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 Things Application.

Mahbub Ul Alam, Rahim Rahmani

Sensors, 2021

Terminology Expansion with Prototype Embeddings: Extracting Symptoms of Urinary Tract Infection from Clinical Text.

Mahbub Ul Alam, Aron Henriksson, Hideyuki Tanushi, Emil Thiman, Pontus Nauclér, Hercules Dalianis

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020

Intelligent context-based healthcare metadata aggregator in internet of medical things platform.

Mahbub Ul Alam, Rahim Rahmani

Proceedings of the 17th International Conference on Mobile Systems and Pervasive Computing (MobiSPC 2020) / The 15th International Conference on Future Networks and Communications (FNC-2020) / The 10th International Conference on Sustainable Energy Information Technology, 2020

Cognitive Internet of Medical Things Architecture for Decision Support Tool to Detect Early Sepsis Using Deep Learning.

Mahbub Ul Alam, Rahim Rahmani

Proceedings of the Biomedical Engineering Systems and Technologies, 2020

Deep Learning from Heterogeneous Sequences of Sparse Medical Data for Early Prediction of Sepsis.

Mahbub Ul Alam, Aron Henriksson, John Karlsson Valik, Logan Morgan Ward, Pontus Nauclér, Hercules Dalianis

Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020), 2020