Machine learning approaches in the therapeutic outcome prediction in major depressive disorder: a systematic review by Veronica Atemnkeng Ntam, Tatjana Huebner, Michael Steffens, Catharina Scholl

“…The objective of the evaluation was to assess applicability of currently published ML-approaches for clinical settings in the EU on the basis of quality, ethical, social, and legal criteria.MethodsWe performed a bibliographic search on PubMed and Google Scholar for studies from January 2016 to December 2024 on ML-applications predicting treatment outcomes in MDD. …”
Get full text

Quantum computing challenges and solutions in software industry—A multivocal literature review by Masaud Salam, Muhammad Ilyas

“…Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. …”
Get full text

Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
Get full text

Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. …”
Get full text

Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
Get full text

Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…Based on this, this study studies the innovation of the teaching model of national vocal music in colleges and universities based on the deep recurrent neural network algorithm and designs the teaching quality evaluation model based on the deep recurrent neural network algorithm. …”
Get full text

MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…At the same time, data scarcity affects the accuracy and comprehensiveness of model evaluation and recommendation. This is a pain point in multimodal recommendation. …”
Get full text

DIFshilling: A Diffusion Model for Shilling Attacks by Weizhi Chen, Xingkong Ma, Bo Liu

“…Many current approaches either fail to capture the natural distribution of real user data or are highly tailored to specific RS algorithms, limiting their general applicability and effectiveness. …”
Get full text

Triple-layered security system: reliable and secured image communications over 5G and beyond networks by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm

“…This paper presents the proposed vision of 5G and beyond security to build a research gap of existing and related technique that lack the adaptation, boosting gradient and complexity analysis, through design and evaluate the adapted and graded security system. This paper focuses on designing a security approach to make up the lacks of existing techniques. …”
Get full text

Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
Get full text

Opposition-based chaotic evolution for optimization by Tianshui Li, Yan Pei

“…The findings support the broader applicability of OBCE in real-world engineering design problems where solution quality and efficiency are critical.…”
Get full text

A Review on Trending Machine Learning Techniques for Type 2 Diabetes Mellitus Management by Panagiotis D. Petridis, Aleksandra S. Kristo, Angelos K. Sikalidis, Ilias K. Kitsas

“…Our work indicates that Gradient Boosting and tree-based models are the most successful ones, the SHAPley and Wrapper algorithms being quite popular feature interpretation and evaluation methods, highlighting urinary markers and dietary intake as emerging diabetes predictors besides the typical invasive ones. …”
Get full text

Chaotic Hénon–Logistic Map Integration: A Powerful Approach for Safeguarding Digital Images by Abeer Al-Hyari, Mua’ad Abu-Faraj, Charlie Obimbo, Moutaz Alazab

“…Performance evaluation in terms of encryption time, throughput, and image quality metrics validates the effectiveness of the proposed integrated approach. …”
Get full text

Capability-driven framework to automate discovery of bounded contexts in large-scale requirements engineering by Shohreh Ajoudanian, Maryam Nooraei Abadeh

“…We also provide the applicability of the approach from various points of view including quality and stability of bounded contexts, average precision, and query assessment. …”
Get full text

Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…This study synthesizes findings from 39 high-quality articles published between 2016 and 2024, evaluating various machine learning (ML), deep learning (DL), regression, and hybrid models in sectors such as construction, healthcare, manufacturing, and real estate. …”
Get full text

A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…As a result, it offers an affordable and practical solution for quality control in peanut production, showing great potential for wide application in the peanut industry.…”
Get full text

Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…Improving translation quality and efficiency is one of the key challenges in the field of Natural Language Processing (NLP). …”
Get full text

Framelet transform based edge detection for straight line detection from remote sensing images by Vidhya Rangasamy, Sulochana Subramaniam

“…Rosenfeld evaluation metric is used to measure the quality of the edge detection methods, which shows the framelet based edge detection produce sound results than other methods. …”
Get full text

Multi-Class Classification Methods for EEG Signals of Lower-Limb Rehabilitation Movements by Shuangling Ma, Zijie Situ, Xiaobo Peng, Zhangyang Li, Ying Huang

“…However, the existing multi-class classification methods for motor imagery EEG (MI-EEG) signals are hindered by low signal quality and limited accuracy, restricting their practical application. …”
Get full text

Exploring State Space Models in LiDAR Point Cloud Segmentation by D. Lu, L. Xu, R. Wang, J. Li

“…To evaluate serialization quality, we proposed two novel indicators—Neighbor Preservation Ratio (NPR) and Sequence Jump Distance (SJD)—which quantify the ability of serialization methods to preserve spatial topology and geometric relationships. …”
Get full text