AlgAlert: A two-level approach for algae bloom prediction using deep learning by Areej Alsini, Amina Saeed, Dawood Amin

“…The framework was developed by benchmarking multiple algorithms and selecting the best-performing regression and classification models for integration. …”
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Can routine data be used to estimate the mental health service use of children and young people living on Gypsy and Traveller sites in Wales? A feasibility study. by Sarah Rees, Richard Fry, Jason Davies, Ann John, Louise Condon

“…Using spatial filtering with data from the Adolescent Mental Health Data Platform (ADP) at Swansea University's SAIL Databank, we created a cohort of Traveller site residents aged 11-25 years old, 2010-2019. ADP algorithms were used to describe health service use, and to estimate incidence and prevalence of common mental disorders (CMD) and self-harm.…”
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YOLO-HF: Early Detection of Home Fires Using YOLO by Bo Peng, Tae-Kook Kim

“…This gap causes object detection algorithms to produce high false positive and false negative rates in research on the early detection of such fires. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Furthermore, metaheuristic algorithms like Smell Agent Optimization and Giant Trevally Optimizer were employed to optimize model's hyperparameters, with the intention of enhancing accuracy and precision in performance estimations. …”
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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

“…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. In addition, it is still unclear if combining histopathological images and molecular data can better predict patients’ survival. …”
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Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy by Guangzong Li, Yuesen Zhang, Di Li, Manhong Zhao, Lin Yin

“…Preoperative clinical and radiological data, including a quantitative assessment of IAC, were systematically collected. Eleven ML algorithms were trained and validated using Python, and external validation and performance evaluations were conducted. …”
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A deep-learning approach to predict reproductive toxicity of chemicals using communicative message passing neural network by Owen He, Daoxing Chen, Yimei Li

“…In independent test sets, ReproTox-CMPNN achieved a mean AUC of 0.946, ACC of 0.857 and F1 score of 0.846, surpassing traditional algorithms to establish itself as a new state-of-the-art model in this field. …”
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Luojia 3-01 Satellite—Real-Time Intelligent Service System for Remote Sensing Science Experiment Satellite by Mi Wang, Qianyu Wu, Jing Xiao, Deren Li, Fang Yang

“…We have proposed the on-orbit real-time processing architecture of Luojia 3-01, addressing the challenges of limited computational and storage resources, particularly in on-orbit processing of vast volumes of remote sensing data, including core algorithmic bottlenecks in “correction-extraction-compression.…”
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Facilitating automated fact-checking: a machine learning based weighted ensemble technique for claim detection by Md. Rashadur Rahman, Rezaul Karim, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Gahangir Hossain, Tetsuya Shimamura

“…To determine the optimal model and feature representation for claim detection, various machine learning algorithms were evaluated using BoW, TF-IDF, Word2Vec, and FastText features. …”
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A robust and statistical analyzed predictive model for drug toxicity using machine learning by Deepak Rawat, Rohit Bajaj, Rachit Manchanda, Ankush Mehta, Prabhu Paramasivam, Suraj Kumar Bhagat, Abinet Gosaye Ayanie

“…An optimized ensembled model is used to contrast the results of seven machine learning algorithms and three deep learning models with regard to state-of-the-art parameters. …”
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Morality on the road: the ADC model in low-stakes traffic vignettes by Michael Pflanzer, Dario Cecchini, Sam Cacace, Veljko Dubljević

“…Our work creates a foundation for stakeholders to integrate human moral judgments into AV decision-making algorithms. Future research should build on these findings by including a more diverse range of participants and exploring the generalizability of the ADC model across different cultural contexts.…”
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Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

“…Our results demonstrate that PCA effectively detected critical variables for soil moisture estimation, with the ANN model outperforming other machine learning algorithms, including Random Forest (RF), Support Vector Regression (SVR), and Gradient Boosting (XGBoost). …”
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Burden of pneumonia and meningitis caused by Streptococcus pneumoniae in China among children under 5 years of age: a systematic literature review. by Ying Chen, Wei Deng, Song-Mei Wang, Qi-Mei Mo, Huan Jia, Qun Wang, Song-Guang Li, Xiang Li, Bao-Dong Yao, Cheng-Jun Liu, Yi-Qiang Zhan, Chen Ji, Anna Lena Lopez, Xuan-Yi Wang

“…<h4>Background and methods</h4>To understand the burden and epidemiology of Streptococcus pneumoniae disease among children between 1 and 59 months of age in China, we conducted a review of literature published between 1980 and 2008 applying standardized algorithms. Because of the absence of population-based surveillance for pneumococcal disease (PD), we identified all-cause pneumonia, bacteremia and meningitis burden, syndromes most commonly associated with S. pneumoniae, and applied the proportion of disease attributable to S. pneumoniae from studies that determined the etiology of these three syndromes to calculate PD burden. …”
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Development of an optimized deep learning model for predicting slope stability in nano silica stabilized soils by Ishwor Thapa, Sufyan Ghani, Prabhu Paramasivam, Mitiku Adare Tufa

“…The results show that RNN-CNN-LSTM, optimized through OPTUNA algorithms, overcomes conventional machine learning models and achieves an accuracy of 99.4% on unseen test data, supported by stable validation trends and robust predictive performance. …”
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Predictive model for initial response to first-line treatment in children with infantile epileptic spasms syndrome by Wenrong Ge, Lin Wan, Zong Wang, Lijun Fu, Guang Yang

“…Random sampling and 5-fold cross-validation were performed, with synthetic minority oversampling technique to correct data imbalance. Machine learning algorithms and evaluation metrics optimised model accuracy and efficacy. …”
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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

“…However, VH polarization is more effective than VV polarization during rainy seasons. While all CPD algorithms showed similar performance, CuSuM had the shortest lag time of up to 9 days, compared to 11 days for PELT and BinSeg. …”
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Data-driven predictive models for sustainable smart buildings by Prabhu Rajaram, Gnana Swathika O․V․

“…It highlights the critical role of energy efficiency and the importance of lowering carbon footprints through the implementation of advanced algorithms, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest, XGBOOST, AdaBoost, and Naive Bayes classifiers. …”
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Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…Deep learning-based spike sorting algorithms are based on power-intensive dot products, which poses challenges for on-chip processing with resource-constrained devices. …”
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A Comparative Study of Data-Driven Prognostic Approaches under Training Data Deficiency by Jinwoo Song, Seong Hee Cho, Seokgoo Kim, Jongwhoa Na, Joo-Ho Choi

“…The performance of these algorithms is compared using the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) datasets, which are made by simulation of turbofan engine performance degradation. …”
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Mapping Harmful Algae Blooms: The Potential of Hyperspectral Imaging Technologies by Fernando Arias, Maytee Zambrano, Edson Galagarza, Kathia Broce

“…An array of HSI techniques, algorithms, and deployment platforms are evaluated, analyzing their efficacy across varied geographical contexts. …”
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