Recent Advancements in Neuroimaging‐Based Alzheimer's Disease Prediction Using Deep Learning Approaches in e‐Health: A Systematic Review by Zia‐Ur‐Rehman, Mohd Khalid Awang, Ghulam Ali, Muhammad Faheem

“…Conclusion DL has considerably improved the accuracy and reliability of AD diagnosis with neuroimaging. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision in remote-sensing images. …”
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Sequential Hybrid Integration of U-Net and Fully Convolutional Networks with Mask R-CNN for Enhanced Building Boundary Segmentation from Satellite Imagery by Rojgar Qarani Ismael, Haval Abduljabbar Sadeq

“…This study investigates the integration of U-Net and Fully Convolutional Networks (FCN) with Mask R-CNN to improve building boundary segmentation using high-resolution satellite imagery. …”
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When Two are Better Than One: Synthesizing Heavily Unbalanced Data by Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes

“…Additionally, privacy is crucial, and it is usually forbidden, or not possible, to share the data of organizations and individuals for creating or improving models.In this paper we propose a framework for private data sharing based on synthetic data generation using <italic>Generative Adversarial Networks (GAN)</italic> that learns the specificities of financial transactions data and generates fictitious data that keeps the utility of the original datasets. …”
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Carbon Sequestration Strategies in Regenerative Agricultural Systems by Leveraging Wireless Sensor Networks for Precision Carbon Management by Al-Jawahry Hassan M., AI_Sadi Hafidh l., Rajasekhar Boddu

“…The predictive models attain greater than 90 percent accuracy of carbon capture efficiency estimation in different regenerative practices, showing a substantial improvement in carbon storage in the soil. …”
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PCES-YOLO: High-Precision PCB Detection via Pre-Convolution Receptive Field Enhancement and Geometry-Perception Feature Fusion by Heqi Yang, Junming Dong, Cancan Wang, Zhida Lian, Hui Chang

“…When compared to YOLOv11s, it increases mAP50 by 1.0% and mAP50–95 by 5.6% while also significantly reducing the model parameters. The performance of PCES-YOLO is also evaluated against mainstream object detection algorithms, including Faster R-CNN, SSD, YOLOv8n, etc. …”
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Using machine learning for the assessment of ecological status of unmonitored waters in Poland by Andrzej Martyszunis, Małgorzata Loga, Karol Przeździecki

“…Since the main goal of Water Framework Directive (WFD) is to improve the quality of water and reach good status in all the water bodies across Europe intensive monitoring program was launched together with water status assessment procedure. …”
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Advancements in deep learning for early diagnosis of Alzheimer’s disease using multimodal neuroimaging: challenges and future directions by Muhammad Liaquat Raza, Muhammad Liaquat Raza, Muhammad Liaquat Raza, Syed Tawassul Hassan, Subia Jamil, Noorulain Hyder, Kinza Batool, Sajidah Walji, Muhammad Khizar Abbas

“…Recent advancements in deep learning algorithms applied to multimodal brain imaging offer promising solutions for improving diagnostic accuracy and predicting disease progression.MethodThis narrative review synthesizes current literature on deep learning applications in Alzheimer’s disease diagnosis using multimodal neuroimaging. …”
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Radiomics capabilities in the interpretation of ultrasound and CT data in patients with chronic kidney disease: A review by Alexandra V. Proskura, Khalil M. Ismailov, Alexander G. Smoleevskiy, Amina I. Salpagarova, Irina N. Bobkova, Andrei M. Shestiuk

“…The article discusses the basics of radiomic methods, including texture analysis of images and the creation of diagnostic models using machine learning algorithms. The advantages of radiomic characteristics, in particular statistical features of order II and higher orders, in assessing interstitial fibrosis and other abnormal changes in the renal parenchyma are discussed in detail. …”
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What happens between first symptoms and first acute exacerbation of COPD – observational study of routine data and patient survey by Alex Bottle, Alex Adamson, Xiubin Zhang, Benedict Hayhoe, Jennifer K Quint

“…Conclusions There has been some improvement over time in chronic obstructive pulmonary disease diagnosis and management, with large changes in prescribing, though patient and system barriers to further improvement exist. …”
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Hand gestures classification of sEMG signals based on BiLSTM-metaheuristic optimization and hybrid U-Net-MobileNetV2 encoder architecture by Khosro Rezaee, Safoura Farsi Khavari, Mojtaba Ansari, Fatemeh Zare, Mohammad Hossein Alizadeh Roknabadi

“…Six standard databases were utilized, achieving an average accuracy of 90.23% with our proposed model, showcasing a 3–4% average accuracy improvement and a 10% variance reduction. …”
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Quantum AI: A Cognitive Machine Learning Technique based on Nurturing Food Security Sustainability Predictive Analysis for Life Science - Bioengineering in Healthcare by Senthil G.A., Monica K.M., Prabha R., Prinslin L., Elavarasi R.

“…Integrating quantum computer models will greatly improve predictive performance and scalability. …”
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The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns by Lianne Grin, Sieglinde Bogaert, Saskia Wijnands, Arnold Besselaar, Marieke van der Steen, Jesse Davis, Benedicte Vanwanseele

“…A relapsed clubfoot typically involves a combination of deformities affecting a child’s movement pattern across multiple joint levels, formed by a complex kinematic chain. Machine learning algorithms have the capacity to analyse such complex nonlinear relationships, offering the potential to train a model that assesses whether a child has relapsed clubfoot based on their movement pattern. …”
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Early-life management practices and their association with dairy herd longevity, productivity, and profitability by Gabriel M. Dallago, Daniel Warner, Elsa Vasseur

“…Cluster stability assessment was used to determine the best clustering algorithm and number of clusters. Associations between herd longevity, productivity, profitability, and early-life management practices were assessed using multivariate linear regression models. …”
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Downscaling Satellite Night-Time Light Imagery While Addressing the Blooming Effect by Nikolaos Tziokas, Ce Zhang, Alexandros Tziokas, Qunming Wang, Peter M. Atkinson

“…Over the past 20 years, improvements in night-time light (NTL) remote sensing have spurred a resurgence of interest in the mapping of human economic activity. …”
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Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis by Subo Zhang, Zhitao Zhu, Zhenfei Yu, Haifeng Sun, Yi Sun, Hai Huang, Lei Xu, Jinxin Wan

“…The quality of these studies was assessed using the Newcastle-Ottawa Scale. Random effect models were used to pool results, and heterogeneity was measured using the I² statistic. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…By incorporating quantum-inspired algorithms into the Grid-Side Converter (GSC) control framework, the strategy dynamically adjusts PI gains using qubit-based probabilistic modeling&#x2014;where control parameters exist simultaneously in multiple potential states, similar to quantum bits existing in both 0 and 1 states concurrently. …”
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KT-Deblur: Kolmogorov–Arnold and Transformer Networks for Remote Sensing Image Deblurring by Baoyu Zhu, Zekun Li, Qunbo Lv, Zheng Tan, Kai Zhang

“…Supported by the Fast Spatial Feature Module (FSFM), it effectively improves the model’s ability to handle complex blur patterns. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…The proposed AKW-MRPK framework achieves up to 92 % accuracy, reduces computational time to as low as 0.875 ms for 25 patients, and demonstrates superior speedup efficiency with a value of 1.9 ms using two computational nodes, consistently outperforming supervised machine learning algorithms and Hadoop-based clusters across these critical metrics. • The AKW-MRPK method selects attributes and accelerates computations for predictions. • Parallelizing polynomial kernels improves accuracy and speed in healthcare data analysis.…”
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