Ensemble classifier selection using multi-objective PSO for fault diagnosis of power transformers. - Abdolrahman Peimankar; Stephen John Weddell; Thahirah Jalal; Andrew Craig Lapthorn (CEC, 2016)

Evolutionary multi-objective fault diagnosis of power transformers. - Abdolrahman Peimankar; Stephen John Weddell; Thahirah Jalal; Andrew Craig Lapthorn (Swarm Evol. Comput., 2017)

Ensemble Learning for Detection of Short Episodes of Atrial Fibrillation. - Abdolrahman Peimankar; Sadasivan Puthusserypady (EUSIPCO, 2018)

Multi-objective ensemble forecasting with an application to power transformers. - Abdolrahman Peimankar; Stephen John Weddell; Thahirah Jalal; Andrew Craig Lapthorn (Appl. Soft Comput., 2018)

An Ensemble of Deep Recurrent Neural Networks for P-wave Detection in Electrocardiogram. - Abdolrahman Peimankar; Sadasivan Puthusserypady (ICASSP, 2019)

Automatic Detection of Cardiac Arrhythmias Using Ensemble Learning. - Abdolrahman Peimankar; Mona Jafar Jajroodi; Sadasivan Puthusserypady (TENCON, 2019)

A deep learning approach for real-time detection of atrial fibrillation. - Rasmus S. Andersen; Abdolrahman Peimankar; Sadasivan Puthusserypady (Expert Syst. Appl., 2019)

DENS-ECG: A deep learning approach for ECG signal delineation. - Abdolrahman Peimankar; Sadasivan Puthusserypady (Expert Syst. Appl., 2021)

Deepaware: A hybrid deep learning and context-aware heuristics-based model for atrial fibrillation detection. - Devender Kumar; Abdolrahman Peimankar; Kamal Sharma; Helena Dominguez; Sadasivan Puthusserypady; Jakob E. Bardram (Comput. Methods Programs Biomed., 2022)

Short-term atrial fibrillation detection using electrocardiograms: A comparison of machine learning approaches. - Masud Shah Jahan; Marjan Mansourvar; Sadasivan Puthusserypady; Uffe Kock Wiil; Abdolrahman Peimankar (Int. J. Medical Informatics, 2022)

Transformers for Detection of Distressed Cardiac Patients with an ICD Based on Danish Text Messages. - Julie Dittmann Weimar Andersen; Marcus Lomstein Jensen; Uffe Kock Wiil; Søren Skovbakke; Ole Skov; Susanne S. Pedersen; Abdolrahman Peimankar; Ali Ebrahimi (BIBM, 2023)

A Machine Learning Approach for Walking Classification in Elderly People with Gait Disorders. - Abdolrahman Peimankar; Trine Straarup Winther; Ali Ebrahimi; Uffe Kock Wiil (Sensors, 2023)

AUD-DSS: a decision support system for early detection of patients with alcohol use disorder. - Ali Ebrahimi; Uffe Kock Wiil; Ruben Baskaran; Abdolrahman Peimankar; Kjeld Andersen; Anette Søgaard Nielsen (BMC Bioinform., 2023)

Pulmonologists-Level lung cancer detection based on standard blood test results and smoking status using an explainable machine learning approach. - Ricco Noel Hansen Flyckt; Louise Sjodsholm; Margrethe Høstgaard Bang Henriksen; Claus Lohman Brasen; Ali Ebrahimi; Ole Hilberg; Torben Frøstrup Hansen; Uffe Kock Wiil; Lars Henrik Jensen; Abdolrahman Peimankar (CoRR, 2024)

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks. - Martin Vibæk; Abdolrahman Peimankar; Uffe Kock Wiil; Daniel Arvidsson; Jan Christian Brønd (Sensors, 2024)

xECG-Beats: an explainable deep transfer learning approach for ECG-based heartbeat classification. - Abdolrahman Peimankar; Ali Ebrahimi; Uffe Kock Wiil (Netw. Model. Anal. Health Informatics Bioinform., 2024)

Prescription data and demographics: An explainable machine learning exploration of colorectal cancer risk factors based on data from Danish national registries. - Abdolrahman Peimankar; Olav Sivertsen Garvik; Bente Mertz Nørgård; Jens Søndergaard; Dorte Jarbøl; Sonja Wehberg; Søren Paludan Sheikh; Ali Ebrahimi; Uffe Kock Wiil; Maria Iachina (Comput. Methods Programs Biomed., 2025)