Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

“…Phytoplankton species biomass data were collected concurrently using standard inverted microscope counts. The SVR algorithm outperformed the other algorithms in predicting phytoplankton abundance and composition in Lake Kinneret, based on the FP measurements. …”
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Evaluation of hydraulic fracturing using machine learning by Ali Akbari, Ali Karami, Yousef Kazemzadeh, Ali Ranjbar

“…This study presents a comprehensive machine learning (ML)-based framework to address this challenge by predicting HF efficiency using three widely used algorithms: Random Forest (RF), Support Vector Machine (SVM), and Neural Networks (NN). …”
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Creating cell-specific computational models of stem cell-derived cardiomyocytes using optical experiments. by Janice Yang, Neil J Daily, Taylor K Pullinger, Tetsuro Wakatsuki, Eric A Sobie

“…We used the genetic algorithm (GA), a heuristic parameter calibration method, to tune ion channel parameters in a mathematical model of iPSC-CM physiology. …”
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Nav2Scene: Navigation-driven fine-tuning for robot-friendly scene generation by Bowei Jiang, Tongyuan Bai, Peng Zheng, Tieru Wu, Rui Ma

“…Specifically, we first introduce path planning score (PPS), which is defined based on the results of the path planning algorithm and can be used to evaluate the robot navigation suitability of a given scene. …”
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Snow Depth Extraction From Time‐Lapse Imagery Using a Keypoint Deep Learning Model by C. M. Breen, W. R. Currier, C. Vuyovich, Z. Miao, L. R. Prugh

“…By integrating computer vision algorithms with snow pole photography, we present a method that uses a keypoint detection model to automatically observe snow height across a network of sites. …”
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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

“…To date, however, targeted efforts at identifying longevity-associated genes have been limited by a lack of predictive power, and useful algorithms for candidate gene-identification have also been lacking.…”
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Semi-analytical modeling and multi-objective optimization of horizontal-well deep borehole heat exchangers by Zhiwei Wang, Xuemei Zhang, Hui Zhang, Hangyu Liu, Shangkuan Yang, Zheng Qian, Jianguo Feng

“…This study develops a high-efficiency semi-analytical model to predict the long-term thermal behavior of horizontal-well deep borehole heat exchangers (DBHEs). …”
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Modelling Ergonomic Hazard Risks in Manual Handling: Insights from Ponorogo’s Traditional Industry by Dian Afif Arifah, Ratih Andhika Akbar Rahma, Triana Harmini, Dhiya Irsyad Hafidz

“…This study aims to develop a model to evaluate and predict ergonomic hazards using a neural network algorithm, focusing on the relationship between manual handling postures and musculoskeletal pain in 12 body regions. …”
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SIGNIFICANCE OF LABORATORY PARAMETERS IN PROGNOSIS OF OUTCOMES OF ACUTE MYOCARDIAL INFARCTION by I. E. Belaya, V. I. Kolomiets, E. K. Musaeva

“…Using decision tree algorithms, we singled out laboratory parameters (attributes) which were subsequently used as input. …”
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5-Fluorouracil Toxicity: Revisiting the Relevance of Pharmacokinetic Parameters by Hans Mielke, Engi Abd Elhady Algharably, Ursula Gundert-Remy

“…Data analysis supported by a decision algorithm suggests that the 5-FU steady-state plasma concentration is a better toxicity predictor than the AUC. …”
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Transcriptional landscape of pleural mesothelioma patients in relation to NF2 gene mutational status by Carlos Orozco-Castaño, Alejandro Mejía-Garcia, Hsuan Megan Tsao, Diego A. Bonilla, Carlos Carvajal-Fierro, Ricardo Bruges-Maya, Alba Combita, Rafael Parra-Medina

“…Immune and stromal infiltration were inferred via the xCell algorithm, cytokine signaling analyzed with Cytosig, and chemotherapeutic sensitivity predicted using the pRRophetic R package. …”
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Spatial and Temporal Variability of Chlorophyll-a and the Modeling of High-Productivity Zones Based on Environmental Parameters: a Case Study for the European Arctic Corridor by Kuzmina Sofia, Lobanova Polina, Chepikova Svetlana Sergeevna

“…Then, using a Random Forest Machine Learning algorithm in the Classifier modification, we created models for each sea to predict the position of high-productivity zones (Chl-a > 1 mg m−3) using environmental parameters. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…A key innovation of this work is the development and application of a selective cleaning algorithm that systematically filters assay data to mitigate noise and inconsistencies inherent in large-scale bioactivity datasets. …”
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Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…When actual qualification rates exceed 88.1%, the model’s regression fit also surpasses 88.1%, indicating strong alignment between predicted and actual performance. (2) Compared with other algorithmic models, the proposed approach achieves a predictive accuracy of over 94.7%. …”
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The spatial extent and the dispersal strategy of species shape the occupancy frequency distribution of stream insect assemblages by I. Szivák, Z. Csabai, D. Schmera, A. Móra

“…Applying a computer program algorithm, we produced samples with different spatial extent. …”
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The diagnostic performance evaluation of the SD BIOLINE HIV/syphilis Duo rapid test in southern Ethiopia: a cross-sectional study by Techalew Shimelis, Endale Tadesse

“…Syphilis serostatus was determined using the Treponema pallidum haemagglutination assay (TPHA).Results The respective sensitivity, specificity, positive predictive value and negative predictive value of the SD BIOLINE HIV/syphilis Duo test were 100, 99.5, 99.5 and 100% for HIV and 97.6, 96, 95.4 and 98% for syphilis testing, respectively. …”
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The impact of environmental variables on reed stands of the intermittent Lake Cerknica, Slovenia: 40 years of change by Nik Ojdanič, Alenka Gaberščik, Igor Zelnik, Aleksandra Golob

“…Decision tree-based data mining using the M5P algorithm effectively identified significant changes in MSAVI2. …”
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Reconstructing the dynamics of HIV evolution within hosts from serial deep sequence data. by Art F Y Poon, Luke C Swenson, Evelien M Bunnik, Diana Edo-Matas, Hanneke Schuitemaker, Angélique B van 't Wout, P Richard Harrigan

“…HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. …”
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Early Warning for Stepwise Landslides Based on Traffic Light System: A Case Study in China by Shuangshuang Wu, Zhigang Tao, Li Zhang, Song Chen

“…Furthermore, leveraging the C5.0 machine learning algorithm, a comparison between the predictive capabilities of the TLS model and a pure rate threshold model reveals that the TLS model achieves a 93% accuracy rate, outperforming the latter by 7 percentage points. …”
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Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism. by John Archer, Jan Weber, Kenneth Henry, Dane Winner, Richard Gibson, Lawrence Lee, Ellen Paxinos, Eric J Arts, David L Robertson, Larry Mimms, Miguel E Quiñones-Mateu

“…In this study, HIV-1 co-receptor usage was predicted for twelve patients scheduled to start a maraviroc-based antiretroviral regimen. …”
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