From lab to field with machine learning – Bridging the gap for movement analysis in real-world environments: A commentary by Carlo Dindorf, Fabian Horst, Djordje Slijepčević, Bernhard Dumphart, Jonas Dully, Matthias Zeppelzauer, Brian Horsak, Michael Fröhlich

“…Finally, automated classification (e) refers to the process of developing a predictive model that assigns input features of data samples to predefined categories or classes using supervised ML. …”
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LiDAR-based individual tree AGB modeling of Pinus kesiya var. langbianensis by incorporating spatial structure by Zhi Liu, Xiaoli Zhang, Yong Wu, Yuansu Xu, Zhengying Cao, Zhibo Yu, Zihang Feng, Hongbin Luo, Chi Lu, Weibin Wang, Guanglong Ou

“…The results showed that AGB models can be effectively constructed based on canopy features alone, even without the inclusion of DBH. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…The model constructs feature vectors for all microbe-drug pairs based on known associations, microbe similarity, and drug similarity. …”
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Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation by Gunjan Shandilya, Sheifali Gupta, Ahmad Almogren, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen

“…By boosting feature propagation, this integration increases the model’s ability to recognize minute patterns in cervical cell images, hence increasing classification accuracy. …”
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Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research by Muskan Kapoor, Enrique Sapena Ventura, Amy Walsh, Alexey Sokolov, Nancy George, Sunita Kumari, Nicholas J. Provart, Benjamin Cole, Marc Libault, Timothy Tickle, Wesley C. Warren, James E. Koltes, Irene Papatheodorou, Irene Papatheodorou, Doreen Ware, Doreen Ware, Peter W. Harrison, Christine Elsik, Galabina Yordanova, Tony Burdett, Christopher K. Tuggle

“…Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. …”
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Explainable Artificial Intelligence for predicting the compressive strength of soil and ground granulated blast furnace slag mixtures by Ahmed Mohammed Awad Mohammed, Omayma Husain, Muyideen Abdulkareem, Nor Zurairahetty Mohd Yunus, Nadiah Jamaludin, Elamin Mutaz, Hashim Elshafie, Mosab Hamdan

“…A database of 200 samples was compiled from the literature, and six ML models—linear regression, decision trees, random forest, artificial neural networks, gradient boosting, and extreme gradient boosting were developed and evaluated. The study highlights the performance of these models and employs SHAP and LIME analysis to evaluate feature importance. …”
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A two phase ensembled deep learning approach of prominent gene extraction and disease risk prediction by Prajna Paramita DEBATA, Alakananda TRIPATHY, Pournamasi PARHI, Smruti Rekha DAS

“… Unlocking novel insights from gene expression of individual patient profiles, clinicians and researchers can discern patterns, biomarkers, and therapies. Moreover, accurate classification enables the development of predictive models for prognosis and treatment response, facilitating personalized medicine approaches. …”
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Freeze-Dried Food in the Diet of Temporary Residents of the Far North by Evgeniy I. Titov, Irina S. Krasnova, Vera I. Ganina, Elena G. Semenova

“…Study objects and methods. The research featured scientific publications on two topics: 1) nutrition and diet of shift workers in the Far North, 2) development of freeze-dried products for long-term storage in extreme conditions. …”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Achieving this objective necessitates the development of highly accurate river water level forecasts. …”
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Optimizing IoT intrusion detection with cosine similarity based dataset balancing and hybrid deep learning by Arvind Prasad, Wael Mohammad Alenazy, Naved Ahmad, Gauhar Ali, Hanaa A. Abdallah, Sadique Ahmad

“…Additionally, we developed a hybrid deep learning model integrating RegNet and FBNet architectures to enhance feature extraction and classification performance. …”
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An adaptive search mechanism with convolutional learning networks for online social media text summarization and classification model by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Hassan Alkhiri, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

“…Abstract The fast development of social media platforms has led to an unprecedented growth of daily short text content. …”
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Understanding EMS response times: a machine learning-based analysis by Peter Hill, Jakob Lederman, Daniel Jonsson, Peter Bolin, Veronica Vicente

“…Advanced ML techniques, including Gradient Boosting models, were applied to evaluate the influence of diverse variables such as call handling times, travel times, weather patterns, and resource availability. Feature engineering was employed to extract meaningful insights, and statistical models were used to validate the relationships between key predictors and response times. …”
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Monitoring and deformation of deep excavation engineering based on DFOS technology and hybrid deep learning by Yanli Peng, Jie Zhao, Yijiang Fan, Cheng Fan

“…Concurrently, as neural network models find application and development in deep excavation displacement prediction, traditional models face challenges such as insufficient accuracy and weak generalization capabilities, failing to meet the high-precision warning demands of practical engineering. …”
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SOPHROLOGY, PSYCHOSOMATICS, DEONTOLOGY AND CREATIVITY by Miroslav Prstačić

“…In this context, culture can be considered as a way of life that encompasses beliefs and religiosity, rituals and various arts (music, theatre, poetry, painting, dance…) mentality and patterns of historically transmitted symbols. At the same time, speech is marked by all physical, psychosomatic, psycho-emotional and spiritual manifestations and is the origin of hermeneutics itself. …”
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Single-cell microbiota phenotyping reveals distinct disease and therapy-associated signatures in Crohn’s disease by Lisa Budzinski, Gi-Ung Kang, René Riedel, Toni Sempert, Leonie Lietz, René Maier, Janine Büttner, Bettina Bochow, Marcell T. Tordai, Aayushi Shah, Amro Abbas, Tanisha Momtaz, Jannike L. Krause, Robin Kempkens, Katrin Lehman, Gitta A. Heinz, Anne E. Benken, Stefanie Bartsch, Kathleen Necke, Ute Hoffmann, Mir-Farzin Mashreghi, Robert Biesen, Tilmann Kallinich, Tobias Alexander, Bosse Jessen, Carl Weidinger, Britta Siegmund, Andreas Radbruch, Anja Schirbel, Benjamin Moser, Hyun-Dong Chang

“…The data were analyzed by machine-learning to assess disease-specific marker patterns in the microbiota phenotype. mMFC captured detailed characteristics of CD microbiota and identified patterns to classify CD patients. …”
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Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorderResearch in context by Stephen Joza, Aline Delva, Christina Tremblay, Andrew Vo, Marie Filiatrault, Max Tweedale, Jean-François Gagnon, Ronald B. Postuma, Alain Dagher, Johannes Klein, Michele Hu, Petr Dusek, Stanislav Marecek, Zsoka Varga, John-Paul Taylor, John T. O'Brien, Michael Firbank, Alan Thomas, Paul C. Donaghy, Stéphane Lehéricy, Marie Vidailhet, Jean-Christophe Corvol, ICEBERG Study Group, Richard Camicioli, Howard Chertkow, Simon Lewis, Elie Matar, Kaylena A. Ehgoetz Martens, Lachlan Churchill, Michael Sommerauer, Sinah Röttgen, Per Borghammer, Karoline Knudsen, Allan K. Hansen, Dario Arnaldi, Beatrice Orso, Pietro Mattioli, Luca Roccatagliata, Oury Monchi, Shady Rahayel, Isabelle Arnulf, Samir Bekadar, Eve Benchetrit, Alexis Brice, Vanessa Brochard, Alizé Chalançon, Benoit Colsch, Florence Cormier-Dequaire, Jean-Christophe Corvol, Virginie Czernecki, Bertrand Degos, Cécile Delorme, Pauline Dodet, Carole Dongmo-Kenfack, Marie-Odile Habert, Farid Ichou, Jonas Ihle, Cécile Galléa, Rahul Gaurav, Marie-Alexandrine Glachant, Manon Gomes, David Grabli, Elodie Hainque, Laetitia Jeancolas, Christelle Laganot, Stéphane Lehéricy, Suzanne Lesage, Smaranda Leu-Semenescu, Richard Levy, Valentine Maheo, Graziella Mangone, Louise Laure Mariani, Aurelie Méneret, Poornima Menon, Fanny Mochel, Vincent Perlbarg, Dijana Petrovska, Fanny Pineau, Nadya Pyatigorskaya, Sophie Rivaud-Pechoux, Emmanuel Roze, Sara Sambin, Julie Socha, Arthur Tenenhaus, Romain Valabregue, Marie Vidailhet, Lydia Yahia-Cherif

“…Interpretation: There are two distinct atrophy progression subtypes in iRBD, with the cortical-first subtype linked to an increased likelihood of developing DLB, while both subtypes were associated with worsening parkinsonian motor features. …”
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Properties of novel biodegradable film from gelatin capsule waste as influenced by various solvents and washing cycles by Pudthaya Kumnerdsiri, Sasina Sanprasert, Anusorn Seubsai, Jaksuma Pongsetkul, Nathdanai Harnkarnsujarit, Saroat Rawdkuen, Samart Sai-ut, Suphat Phongthai, Piyangkun Lueangjaroenkit, Ekasit Onsaard, Ali Muhammed Moula Ali, Thomas Karbowiak, Wanli Zhang, Passakorn Kingwascharapong

“…FTIR spectroscopy revealed differences in bands and patterns between control film (GCWF) and washed films (GCWF Alc and GCWF W). …”
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Identify suitable artificial groundwater recharge zones using hybrid deep learning models by Navaz Khalillollahi, Mohsen Isari, Hamed Faroqi, Kaywan Othman Ahmed, Kamran Nobakht Vakili, Miklas Scholz, Saad Sh. Sammeng

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GradCAM-PestDetNet: A deep learning-based hybrid model with explainable AI for pest detection and classification by Ramitha Vimala, Saharsh Mehrotra, Satish Kumar, Pooja Kamat, Arunkumar Bongale, Ketan Kotecha

“…The GradCAM-PestDetNet methodology utilizes object detection models like YOLOv8m, YOLOv8s and YOLOv8n, alongside transfer learning techniques such as VGG16, ResNet50, EfficientNetB0, MobileNetV2, InceptionV3 and DenseNet121 for feature extraction. Additionally, Vision Transformers (ViT) and Swim Transformers were explored for their ability to process complex data patterns. …”
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MobilitApp: A Deep Learning-Based Tool for Transport Mode Detection to Support Sustainable Urban Mobility by Gerard Caravaca Ibanez, Luis J. de la Cruz Llopis, Adrian Catalin Diaconeasa, Alberto Bazan Guillen, Monica Aguilar Igartua

“…By analyzing travel patterns, transport modes, and mode-switching behaviors, it delivers actionable insights to city planners, aiding in the enhancement of urban mobility, promotion of sustainable development, and transition to greener cities.…”
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