Thinned ECOC Decomposition for Gene Expression Based Cancer Classification. - Nima Hatami (ISDA (1), 2008)

Error Correcting Output Codes Using Genetic Algorithm-Based Decoding. - Nima Hatami; Saeed Seyedtabaii (NCM (1), 2008)

Mixture of Random Prototype-Based Local Experts. - Giuliano Armano; Nima Hatami (HAIS (1), 2010)

Random Prototype-based Oracle for Selection-fusion Ensembles. - Giuliano Armano; Nima Hatami (ICPR, 2010)

A New Gene Selection Method Based on Random Subspace Ensemble for Microarray Cancer Classification. - Giuliano Armano; Camelia Chira; Nima Hatami (PRIB, 2011)

Run-Time Performance Analysis of the Mixture of Experts Model. - Giuliano Armano; Nima Hatami (Computer Recognition Systems 4, 2011)

An Improved Mixture of Experts Model: Divide and Conquer Using Random Prototypes. - Giuliano Armano; Nima Hatami (Ensembles in Machine Learning Applications, 2011)

Ensemble of Binary Learners for Reliable Text Categorization with a Reject Option. - Giuliano Armano; Camelia Chira; Nima Hatami (HAIS (1), 2012)

Hybrid Evolutionary Algorithm with a Composite Fitness Function for Protein Structure Prediction. - Camelia Chira; Nima Hatami (IDEAL, 2012)

Error-Correcting Output Codes for Multi-Label Text Categorization. - Giuliano Armano; Camelia Chira; Nima Hatami (IIR, 2012)

A Route Confidence Evaluation Method for Reliable Hierarchical Text Categorization - Nima Hatami; Camelia Chira; Giuliano Armano (CoRR, 2012)

Thinned-ECOC ensemble based on sequential code shrinking. - Nima Hatami (Expert Syst. Appl., 2012)

Some proposals for combining ensemble classifiers. - Nima Hatami (2012)

Classifiers with a reject option for early time-series classification. - Nima Hatami; Camelia Chira (CIEL, 2013)

ECOC-Based Training of Neural Networks for Face Recognition. - Nima Hatami; Reza Ebrahimpour; Reza Ghaderi (CoRR, 2013)

Diverse accurate feature selection for microarray cancer diagnosis. - Nima Hatami; Camelia Chira (Intell. Data Anal., 2013)

Special issue on "Innovative knowledge based techniques in pattern recognition". - Manuel Graña; Michal Wozniak 001; Nima Hatami (Pattern Recognit. Lett., 2013)

Automatic Identification of Retinal Arteries and Veins in Fundus Images using Local Binary Patterns. - Nima Hatami; Michael H. Goldbaum (CoRR, 2016)

Classification of time-series images using deep convolutional neural networks. - Nima Hatami; Yann Gavet; Johan Debayle (ICMV, 2017)

Magnetic Resonance Spectroscopy Quantification Using Deep Learning. - Nima Hatami; Michaël Sdika; Hélène Ratiney (MICCAI (1), 2018)

Bag of recurrence patterns representation for time-series classification. - Nima Hatami; Yann Gavet; Johan Debayle (Pattern Anal. Appl., 2019)

Deep Multi-Resolution Dictionary Learning for Histopathology Image Analysis. - Nima Hatami; Mohsin Bilal; Nasir M. Rajpoot (CoRR, 2021)

CNN-LSTM Based Multimodal MRI and Clinical Data Fusion for Predicting Functional Outcome in Stroke Patients. - Nima Hatami; Tae-Hee Cho; Laura Mechtouff; Omer Faruk Eker; David Rousseau; Carole Frindel (EMBC, 2022)

A Novel Autoencoders-LSTM Model for Stroke Outcome Prediction Using Multimodal MRI Data. - Nima Hatami; Laura Mechtouff; David Rousseau; Tae-Hee Cho; Omer Faruk Eker; Yves Berthezene; Carole Frindel (ISBI, 2023)

DeepFEL: Deep Fastfood Ensemble Learning for Histopathology Image Analysis. - Nima Hatami (CoRR, 2023)

A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge. - Ezequiel de la Rosa; Mauricio Reyes 001; Sook-Lei Liew; Alexandre Hutton; Roland Wiest; Johannes Kaesmacher; Uta Hanning; Arsany Hakim; Richard Zubal; Waldo Valenzuela; David Robben; Diana Maria Sima; et al. (CoRR, 2024)

Fusion of Dwi Image and Clinical Variables for Stroke Outcome Prediction Using Tabular Transformer. - Mingtian Liu; Nima Hatami; Laura Mechtouff; Tae-Hee Cho; Carole Lartizien; Carole Frindel (ISBI, 2025)