Deep hybrid architectures for binary classification of medical breast cancer images

H Zerouaoui, A Idri - Biomedical Signal Processing and Control, 2022 - Elsevier
The diagnosis of breast cancer in the early stages significantly decreases the mortality rate
by allowing the choice of adequate treatment. This study developed and evaluated twenty …

Software development effort estimation using regression fuzzy models

AB Nassif, M Azzeh, A Idri… - Computational intelligence …, 2019 - Wiley Online Library
Software effort estimation plays a critical role in project management. Erroneous results may
lead to overestimating or underestimating effort, which can have catastrophic consequences …

Heterogeneous ensemble model to optimize software effort estimation accuracy

SS Ali, J Ren, K Zhang, J Wu, C Liu - IEEE Access, 2023 - ieeexplore.ieee.org
The software industry has experienced rapid expansion in recent years, with software
development now essential to the success of many multinational corporations. The demand …

Investigating the use of random forest in software effort estimation

H Mustapha, N Abdelwahed - Procedia computer science, 2019 - Elsevier
Over the last two decades, there has been an important increase in studies dealing with the
software development effort estimation (SDEE) using machine learning (ML) techniques that …

Deep hybrid architectures for diabetic retinopathy classification

C Lahmar, A Idri - Computer Methods in Biomechanics and …, 2023 - Taylor & Francis
Diabetic retinopathy (DR) is the most severe ocular complication of diabetes. It leads to
serious eye complications such as vision impairment and blindness. A computer-aided …

Parametric software effort estimation based on optimizing correction factors and multiple linear regression

HLTK Nhung, V Van Hai, R Silhavy, Z Prokopova… - Ieee …, 2021 - ieeexplore.ieee.org
Context: Effort estimation is one of the essential phases that must be accurately predicted in
the early stage of software project development. Currently, solving problems that affect the …

On the value of deep learning for diagnosing diabetic retinopathy

C Lahmar, A Idri - Health and Technology, 2022 - Springer
Diabetic retinopathy (DR) is one of the main causes of vision loss around the world. The
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …

Effect of cluster size distribution on clustering: a comparative study of k-means and fuzzy c-means clustering

K Zhou, S Yang - Pattern Analysis and Applications, 2020 - Springer
Data distribution has a significant impact on clustering results. This study focuses on the
effect of cluster size distribution on clustering, namely the uniform effect of k-means and …

Software development effort estimation using boosting algorithms and automatic tuning of hyperparameters with Optuna

M Hassanali, M Soltanaghaei… - Journal of Software …, 2024 - Wiley Online Library
Considering the increasing need for software projects, estimating software development
efforts is essential and can lead to improved project delivery quality. Machine learning …

Systematic map and review of predictive techniques in diabetes self-management

TEL Idrissi, A Idri, Z Bakkoury - International Journal of Information …, 2019 - Elsevier
Data mining (DM) provides powerful tools to extract knowledge from large volumes of data
offering valuable information to decision making. The extracted knowledge can be used for …