Building health systems capable of leveraging AI: applying Paul Farmer’s 5S framework for equitable global health by Liam G. McCoy, Azra Bihorac, Leo Anthony Celi, Matthew Elmore, Divya Kewalramani, Teddy Kwaga, Nicole Martinez-Martin, Renata Prôa, Joel Schamroth, Jonathan D. Shaffer, Alaa Youssef, Amelia Fiske

“…A broad base of critical scholarship has highlighted important issues with healthcare AI, including algorithmic bias and inequitable and inaccurate model outputs. …”
Get full text

LAF: Enhancing person re-identification via Latent-Assisted Feature Fusion by Minglang Li, Zhiyong Tao, Sen Lin, Kaihao Feng

“…Extensive experiments on five large-scale person re-identification benchmarks demonstrate that LAF consistently improves the performance of existing algorithms. Compared to state-of-the-art methods, LAF achieves superior results, including an mAP of 89.6% and Rank-1 accuracy of 95.9% on the Market1501 dataset, and an mAP of 63.3% with Rank-1 accuracy of 84.1% on the MSMT17 dataset. …”
Get full text

Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…By adjusting the propagation environment using reconfigurable reflecting elements, intelligent reflecting surfaces (IRSs) have become potential techniques used to improve the efficiency of wireless communication networks. …”
Get full text

Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

“…The early detection of brain tumors is critical for improving clinical outcomes and patient survival. However, medical imaging datasets frequently exhibit class imbalance, posing significant challenges for traditional classification algorithms that rely on balanced data distributions. …”
Get full text

Preliminary study: Data analytics for predicting medication adherence in Malaysian arthritis patients by Firdaus Aziz, Shubathira Sooriamoorthy, Bryan Liew, Sharifah M. Syed Ahmad, Wei Wen Chong, Sorayya Malek, Adliah Mhd Ali

“…These variables were used to build predictive models for medication adherence. Results Results from machine learning algorithms showed varied performance. …”
Get full text

Teaching design students machine learning to enhance motivation for learning computational thinking skills by Hung-Hsiang Wang, Chun-Han Ariel Wang

“…Students using Weka spent more time focusing on model training and tended to improve their algorithmic thinking, and the introduction of Weka appeared to enhance their motivation to learn. …”
Get full text

Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology by Yan Ye, Yuanyuan Chen, Jiajia Pan, Peipei Li, Feifei Ni, Haizhen He

“…Conclusion Our results indicate that SEResNet101 offers a promising enhancement over existing screening methods, integrating advanced deep learning algorithms to significantly improve the precision of cervical lesion classification. …”
Get full text

Enhancing Crop Health: Advanced Machine Learning Techniques for Prediction Disease in Palm Oil Tree by Nandy Manish, Kumar Yalakala Dinesh

“…The culmination of ths work will improve the accuracy and adoption to other crops of these better models and thus improve the resilience of global agriculture to disease.…”
Get full text

Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…Importantly, the term “quantum-inspired” refers to classical algorithms that emulate quantum principles—such as probabilistic reasoning and solution diversity—without employing quantum hardware. …”
Get full text

Development experience of information system for ranking of academic and pedagogical staff by A. A. Chernousov, E. V. Vavilova

“…Experience in the implementation of the rating system in Plekhanov Russian University of Economics showed that the independent automated assessment of the activity efficiency of officers allows to improve the mechanism of planning and personnel management system, allows to create model of stimulation of the types of activity influencing increase of the place of University in the Russian and international ratings, and also creates conditions for positive dynamics of growth of level of qualification of academic and pedagogical staff. …”
Get full text

Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

“…Noisy data is a prevalent issue in data mining, significantly impacting the performance of classification algorithms. Mathematical methods are crucial in tackling this obstacle, particularly in optimizing noise detection and data preprocessing. …”
Get full text

Severity assessment of burned skin based on anisotropy of optical coherence elastography by Heng Liu, Di Yang, Renfei Jia, Weike Wang, Lili Shao, Quanzhong Liu, Yanmei Liang

“…In this study, we used OCE to reveal the shear modulus and anisotropy parameters of burned skin before and after burning. A porcine skin burn model was constructed at a series of burned time durations and tested by elastic anisotropy imaging. …”
Get full text

Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…Based on these findings, targeted action plans were developed to support continuous improvement and operational effectiveness. This research advances the state of the art by introducing an explainable AI model capable of identifying the most impactful failures affecting customer satisfaction in large-scale retail operations. …”
Get full text

A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…Such algorithms provided prediction accuracies of 0.963, 0.739, 0.773, 0.866, and 0.866 sequentially. …”
Get full text

ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…The results demonstrate that ML-SOHOT enhanced the HO optimization performance significantly and surpassed the competitive algorithms. Furthermore, ML-SOHOT achieves an average HO performance improvement of up to 96% compared to competitive algorithms from the literature. …”
Get full text

Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Innovative segmentation techniques and multimodal imaging models have further enhanced healthcare efficiency by reducing physician workload and improving diagnostic accuracy. …”
Get full text

Weed-crop dataset in precision agriculture: Resource for AI-based robotic weed control systemsMendeley Data by Arjun Upadhyay, Sunil G. C, Maria Villamil Mahecha, Joseph Mettler, Kirk Howatt, William Aderholdt, Michael Ostlie, Xin Sun

“…To achieve this, a real field dataset was collected under diverse environmental conditions to mimic the natural environment and exhibits the variability in datasets. This aims to improve the accuracy of deep learning models for real time weed identification in precision agriculture. …”
Get full text

Dual-Path Large Kernel Learning and Its Applications in Single-Image Super-Resolution by Zhen Su, Mang Sun, He Jiang, Xiang Ma, Rui Zhang, Chen Lv, Qiqi Kou, Deqiang Cheng

“…To enhance the performance of super-resolution models, neural networks frequently employ module stacking. …”
Get full text

Development of GUI-Driven AI Deep Learning Platform for Predicting Warpage Behavior of Fan-Out Wafer-Level Packaging by Ching-Feng Yu, Jr-Wei Peng, Chih-Cheng Hsiao, Chin-Hung Wang, Wei-Chung Lo

“…Traditional electronic engineers often face difficulties in implementing AI-driven models due to the specialized programming and algorithmic expertise required. …”
Get full text

Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels by Mohammad Hassan Adeli, Dariush Abbasi-Moghadam, Hossein Fotouhi, S. Mohammad Razavizadeh

“…Results demonstrate the superiority of our proposed design compared to the conventional scenarios with equal power allocation and fixed PS ratio algorithms with about 2 to 5 times EE improvements. …”
Get full text