Using weak signals to predict spontaneous breathing trial success: a machine learning approach by Romain Lombardi, Mathieu Jozwiak, Jean Dellamonica, Claude Pasquier

“…The study focuses on the development of ML algorithms to predict the success of the spontaneous breathing trial based on a combination of discrete variables and biosignals (time series) recorded during the 24 h prior to the SBT. …”
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Comparative analysis of high-resolution UAV photogrammetry and terrestrial laser scanning for detecting and quantifying urban vegetation changes by O. B. Shafaat, H. Kauhanen, A. Julin, M. Vaaja

“…Notably, many existing methods involve rasterizing point clouds as DSM which results in the loss of significant information. …”
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G-OnRamp: Generating genome browsers to facilitate undergraduate-driven collaborative genome annotation. by Luke Sargent, Yating Liu, Wilson Leung, Nathan T Mortimer, David Lopatto, Jeremy Goecks, Sarah C R Elgin

“…Despite advances in computational gene prediction algorithms, most eukaryotic genomes still benefit from manual gene annotation. …”
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The future of immunohistochemistry: advancing precision medicine through artificial intelligence-driven spatial proteomics and multiplexed diagnostic technologies by Ruby Dhar, Arun Kumar, Subhradip Karmakar

“…The integration of AI algorithms automates the quantification of biomarkers, minimizes subjectivity in interpretations, and speeds up turnaround times in high-volume labs. …”
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A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation by Binsheng He, Lixia Wang, Wenjing Zhou, Haiyan Liu, Yingxuan Wang, Kebo Lv, Kunhui He

“…Predicting the survival of CRC patients not only enhances understanding of their life expectancies but also aids clinicians in making informed decisions regarding suitable adjuvant treatments. Although there are many clinical, genomic, and transcriptomic studies on this hot topic, only a few studies have explored the direction of integrating advanced deep learning algorithms and histopathological images. …”
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Assessing change point detection methods to enable robust detection of early stage Artisanal and Small-Scale mining (ASM) in the tropics using Sentinel-1 time series data by Mensah Isaac Obour, Barrett Brian, Cahalane Conor

“…Artisanal and Small-Scale mining (ASM) provides essential livelihoods for many in developing countries but often lacks regulation, leading to environmental issues such as water pollution and deforestation. …”
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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. …”
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A refined lion optimizer for deep learning by Jian Rong, Chenhao Ma, Qinghui Zhang, Yong Cao, Weili Kou

“…Abstract Optimization algorithms play a fundamental role in training neural networks. …”
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Development of time to event prediction models using federated learning by Rasmus Rask Kragh Jørgensen, Jonas Faartoft Jensen, Tarec El-Galaly, Martin Bøgsted, Rasmus Froberg Brøndum, Mikkel Runason Simonsen, Lasse Hjort Jakobsen

“…Method We propose two methods for training time-to-event prediction models based on distributed data, relying on FL algorithms, for time-to-event prediction models. Both approach incorporates steps to allow prediction of individual-level survival curves, without exposing individual-level event times. …”
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OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis. by Greg Finak, Jacob Frelinger, Wenxin Jiang, Evan W Newell, John Ramey, Mark M Davis, Spyros A Kalams, Stephen C De Rosa, Raphael Gottardo

“…Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. …”
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The Evolution of Service Ecosystems Based on the Lotka–Volterra Model by Binbin Shi, Yu Li, Tingting Liang, Xixi Sun, Liquan Cui, Haonan Zhang, Yuyu Yin

“…Diversification and business expansion have become key strategies for modern business development, prompting many large companies to move from singular service models to diversified service strategies, ultimately evolving into comprehensive service ecosystems. …”
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Efficiency Ranking of Photovoltaic Microinverters and Energy Yield Estimations for Photovoltaic Balcony Power Plants by Stefan Krauter, Jörg Bendfeld

“…Yield rankings sometimes differ from efficiency rankings due to the use of different MPPT algorithms with different MPP approach speeds and accuracies. …”
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Multi-level User Interest and Multi-intent Fusion for Next Basket Recommendation by WEI Chuyuan, YUAN Baojie, WANG Changdong

“…The existing next-basket recommendation algorithms fail to adequately disentangle multi-intents within baskets and consider user interests or intents from only a single level, thereby     resulting in suboptimal recommendation performance. …”
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Neighbor Similarity Based Agglomerative Method for Community Detection in Networks by Jianjun Cheng, Xing Su, Haijuan Yang, Longjie Li, Jingming Zhang, Shiyan Zhao, Xiaoyun Chen

“…The results show that the proposed method can detect high-quality community structures from networks steadily and efficiently and outperform the comparison algorithms significantly.…”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Phish-Jam utilizes a super learner ensemble that combines predictions from diverse Machine Learning (ML) algorithms to classify legitimate and phishing websites. …”
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A Comprehensive Review on Sensor-Based Electronic Nose for Food Quality and Safety by Teodora Sanislav, George D. Mois, Sherali Zeadally, Silviu Folea, Tudor C. Radoni, Ebtesam A. Al-Suhaimi

“…This has led to the emergence of many research works that focus on automating and streamlining the assessment of food quality. …”
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Challenges and opportunities for precision livestock farming applications in the rabbit production sector by Tomás Norton, María Cambra-López

“…Precision livestock farming (PLF) is an established field in many livestock sectors. However, when it comes to rabbit production, it is still emerging. …”
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Dengue Contingency Planning: From Research to Policy and Practice. by Silvia Runge-Ranzinger, Axel Kroeger, Piero Olliaro, Philip J McCall, Gustavo Sánchez Tejeda, Linda S Lloyd, Lokman Hakim, Leigh R Bowman, Olaf Horstick, Giovanini Coelho

“…<h4>Background</h4>Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. …”
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Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Our experimental study, based on real-world energy data, demonstrates that our proposed solutions are efficient both in terms of cost savings achieved by the peers and in terms of communication and computing requirements. Our scalable algorithms thus provide one core building block for practical and data-efficient peer-to-peer energy sharing communities within large-scale optimization systems.…”
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GDDKIA xml service, road traffic incidents data: availability and quality research by Natalia Dziuba, Stanisław Szombara

“…To improve accuracy, additional algorithms were applied that automatically corrected the position of the points to match the nearest roads. …”
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