A Bioinert Hydrogel Framework for Precision 3D Cell Cultures: Advancing Automated High‐Content and High‐Throughput Drug Screening by Hyunsu Jeon, Tiago Thomaz Migliati Zanon, James Carpenter, Aliciana Ilias, Yamil Colón, Yichun Wang

“…Enhanced drug testing efficiency has driven the prominence of high‐content and high‐throughput screening (HCHTS) in drug discovery and development. …”
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A novel bivariate regression model derived from the clayton copula and the Odd Dagum-G family and its application by Julius Kwaku Adu-Ntim, Akoto Yaw Omari-Sasu, Maxwell Akwasi Boateng, Isaac Adjei Mensah

“…This study presents a new bivariate regression model that is generated from the Clayton Copula and the Odd Dagum-G (OddD-G) family. Many of the current bivariate regression models including those based on the bivariate normal and t-distributions assume symmetric dependencies, therefore restricting their relevance to real-world data where dependence structures are commonly asymmetric or bimodal. …”
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Unravelling the infodemic: a systematic review of misinformation dynamics during the COVID-19 pandemic by Sudip Bhattacharya, Alok Singh, Alok Singh

“…Data were extracted, thematically coded, and synthesized. …”
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An in-depth exploration of supervised and semi-supervised learning on face recognition by Purnawansyah, Wibawa Aji Prasetya, Widiyaningtyas Triyanna, Haviluddin, Darwis Herdianti, Azis Huzain

“…Experimental outcomes reveal that the performance of models depends on the dataset partitioning strategies and the type of algorithms used. …”
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Acoustic Sensors data transmission integrity and endurance with IoT-enabled location-aware framework by Shujaat Ali, Muhammad Nadeem, Sheeraz Ahmed, Faheem Khan, Murad Khan, Abdullah Alharbi

“…Specifically, ILAF achieved a packet delivery ratio (PDR) of 99%, which outperforms energy-efficient region-based source distributed routing algorithm (EERSDRA) (98%) and energy-efficient geo-opportunistic routing protocols (EEGORP) (96%). …”
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Method for designing specialized computing systems based on hardware and software co-optimization by I. Е. Tarasov, P. N. Sovietov, D. V. Lulyava, D. I. Mirzoyan

“…The development of such systems requires both the selection of the relevant high-demand tasks and the application of design techniques for achieving desired indicators within the developed specializations at very large scales of integration. …”
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Machine Learning and Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring by Sehat Ullah, Sangeen Khan, David Vanecek, Inam Ur Rehman

“…It evaluated six ML algorithms to determine the most accurate model. The models were trained and tested by using a dataset combining two public datasets and real-world data collected by healthcare providers. …”
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Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…Results One of our unique discoveries is that, using our datasets, we verified that our proposed algorithm, DMTCNN, could appropriately categorize dissimilar brain disorders. …”
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Shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity. by J R Managbanag, Tarynn M Witten, Danail Bonchev, Lindsay A Fox, Mitsuhiro Tsuchiya, Brian K Kennedy, Matt Kaeberlein

“…In addition to facilitating an improved understanding of the basic mechanisms of aging, such genes represent potential targets for therapeutic intervention in multiple age-associated diseases, including cancer, heart disease, diabetes, and neurodegenerative disorders. …”
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Cost-Effectiveness of Automated Digital Microscopy for Diagnosis of Active Tuberculosis. by Swati Jha, Nazir Ismail, David Clark, James J Lewis, Shaheed Omar, Andries Dreyer, Violet Chihota, Gavin Churchyard, David W Dowdy

“…The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain.…”
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Real-World Application of Digital Morphology Analyzers: Practical Issues and Challenges in Clinical Laboratories by Hanah Kim, Mina Hur, Giuseppe d’Onofrio, Gina Zini

“…However, recognizing rare and dysplastic cells remains challenging due to variable algorithmic performances, which affect diagnostic reliability. …”
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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…This review discusses the potential of artificial intelligence (AI), particularly machine learning (ML) and its subset, deep learning (DL), in advancing the genetic improvement of Solanaceous crops. …”
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Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models by C Fanelli, J Giroux, J Stevens

“…At the future electron–ion collider (EIC), the ePIC detector will feature a dual Ring Imaging Cherenkov (RICH) detector in the hadron direction, a Detector of Internally Reflected Cherenkov (DIRC) in the barrel, and a proximity focus RICH in the electron direction. …”
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Disentangling High-Paced Alternating I/O in Gaze-Based Interaction by Yulia G. Shevtsova, Artem S. Yashin, Sergei L. Shishkin, Anatoly N. Vasilyev

“…Gaze-based input to machines utilizes the ability of eye-gaze to serve as a user’s “output.” However, gaze should also support information flow in the opposite direction, namely, “input” to the user’s visual system from a machine’s output. …”
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Development and Validation of a Machine Learning Model for Predicting Long-Term Depression Risk in ACS Patients After PCI: A Retrospective Cohort Study by Lv H, Sun F, Zhang Y, Zhou X

“…Our goal was to predict who might develop depression in the year after their procedure. …”
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An intelligent adaptive neuro-fuzzy based control for multiport DC-AC converter with differential power processing converter for hybrid renewable power generation systems by S. Shanmugam, A. Sharmila

“…Complementary DPP converters process only the differential power, thereby significantly reducing total power consumption and conversion losses. …”
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Intelligent Fault Diagnosis Across Varying Working Conditions Using Triplex Transfer LSTM for Enhanced Generalization by Misbah Iqbal, Carman K. M. Lee, Kin Lok Keung, Zhonghao Zhao

“…While various machine/deep learning algorithms have been employed extensively for diagnosing faults in bearings and gears, the scarcity of data and the limited availability of labels have become a major bottleneck in developing data-driven diagnosis approaches, restricting the accuracy of deep networks. …”
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Gorilla troops optimization with deep learning based crop recommendation and yield prediction by A. Punitha, V. Geetha

“…Despite the significant advancements of Deep Learning (DL) models in crop recommendation, hyperparameter tuning using metaheuristic algorithms becomes essential for enhanced performance. …”
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Judges versus artificial intelligence in juror decision-making in criminal trials: Evidence from two pre-registered experiments. by Eiichiro Watamura, Yichen Liu, Tomohiro Ioku

“…However, whether this leads to improved decision-making quality remains an open question, as objectivity (a strength of AI) and emotional considerations (a safeguard for fairness) may interact in complex ways during juror deliberations. …”
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Deep Learning-Based Adaptive Downsampling of Hyperspectral Bands for Soil Organic Carbon Estimation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…Existing dimensionality reduction techniques, such as fixed-interval downsampling and autoencoders, either risk discarding informative bands or disrupt spectral continuity, limiting their effectiveness for models like one-dimensional convolutional neural networks (1D-CNNs) that rely on local spectral patterns. …”
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