Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants by Mohamed Farag Taha, Hanping Mao, Samar Mousa, Lei Zhou, Yafei Wang, Gamal Elmasry, Salim Al-Rejaie, Abdallah Elshawadfy Elwakeel, Yazhou Wei, Zhengjun Qiu

“…Also, features selected by the DAE showed better performance compared to features extracted using both genetic algorithms (GAs) and sequential forward selection (SFS). …”
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Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis by Martina Votto, Annalisa De Silvestri, Lorenzo Postiglione, Maria De Filippo, Sara Manti, Stefania La Grutta, Gian Luigi Marseglia, Amelia Licari

“…Conclusion This study provides the most comprehensive assessment of AI-based algorithms in predicting paediatric asthma exacerbations to date. …”
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Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…The review also categorizes findings by their specific applications and contexts, providing valuable insights into <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>&#x2019;s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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Feasibility of Digitally Identifying and Minimizing Stressors in Palliative Care Workplaces by Measuring Stress Continuously for Nurses Through Wearable Sensors (DiPa): Protocol fo... by Aaron Seehausen, Wencke Chodan, Florian Höpfner, Carolin Schneider, Sabine Felser, Hugo Murua Escobar, Mario Aehnelt, Christian Junghanss

“…These cause high stress levels and burden on the nursing staff, resulting in an early exit from working life because of physical or psychological disorders like burnout. …”
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Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members by Nataly Buslón, Davide Cirillo, Oriol Rios, Simón Perera del Rosario

“…ResultsAnalysis of the focus group discussions revealed several critical barriers impacting the integration of AI in personalized medicine for trans people, including concerns around data privacy, biases in algorithmic decision-making, and the lack of tailored health care data reflective of trans experiences. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…We hope to identify high-risk patients for early intervention to reduce the incidence of HF and improve their quality of life.…”
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An Immune-Related Prognostic Classifier Is Associated with Diffuse Large B Cell Lymphoma Microenvironment by Xiao-Jie Liang, Rui-ying Fu, He-nan Wang, Jing Yang, Na Yao, Xin-di Liu, Liang Wang

“…Diffuse large B cell lymphoma (DLBCL) is a life-threatening malignant tumor characterized by heterogeneous clinical, phenotypic, and molecular manifestations. …”
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Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…This review explores current progress, persistent challenges, and the transformative potential of nanotechnology in reshaping diabetes diagnosis and treatment and improving patient quality of life.…”
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Organization experience of diagnostic and medicosocial services for patients with Charcot—Marie—Tooth disease in Krasnoyarsk region by E. V. Glushchenko, N. A. Shnayder, E. A. Kantimirova, E. A. Kozulina, M. I. Voevoda, V. N. Maksimov, A. A. Allakhverdyan

“…Goal of the study was the development of evidence-based diagnostic and treatment algorithms using patients with CMT (for example, in Krasnoyarsk Territory).Materials and methods: A total of 324 people. …”
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Approach to Neonates and Young Infants with Fever without a Source Who Are at Risk for Severe Bacterial Infection by Susanna Esposito, Victoria Elisa Rinaldi, Alberto Argentiero, Edoardo Farinelli, Marta Cofini, Renato D’Alonzo, Antonella Mencacci, Nicola Principi

“…To favour the differentiation between low- and high-risk infants, several algorithms based on analytical and clinical parameters have been developed. …”
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Challenges, Difficulties, and Delayed Diagnosis of Multiple Myeloma by Tugba Zorlu, Merve Apaydin Kayer, Nazik Okumus, Turgay Ulaş, Mehmet Sinan Dal, Fevzi Altuntas

“…<b>Findings:</b> Delayed diagnosis can lead to presentation at advanced disease stages associated with life-threatening complications and shorter progression-free survival. …”
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Simulating the Deterioration Behavior of Tunnel Elements Using Amalgamation of Regression Trees and State-of-the-Art Metaheuristics by Eslam Mohammed Abdelkader, Abobakr Al-Sakkaf, Moaaz Elkabalawy, Abdelhady Omar, Ghasan Alfalah

“…Leveraging metaheuristic algorithms’ strengths, the developed method jointly optimizes critical regression tree hyperparameters and identifies the most relevant features for deterioration prediction. …”
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High-levels of acquired drug resistance in adult patients failing first-line antiretroviral therapy in a rural HIV treatment programme in KwaZulu-Natal, South Africa. by Justen Manasa, Richard J Lessells, Andrew Skingsley, Kevindra K Naidu, Marie-Louise Newell, Nuala McGrath, Tulio de Oliveira, Southern African Treatment and Resistance Network

“…Genotypic resistance testing was performed using the in-house SATuRN/Life Technologies system. Sequences were analysed and genotypic susceptibility scores (GSS) for standard second-line regimens were calculated using the Stanford HIVDB 6.0.5 algorithms.…”
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EXPERIENCE OF SUCCESSFUL ACNEFORM ERUPTIONS TREATMENT IN PATIENT WITH MULTIPLE MELANOMA by O. V. Minkina, A. S. Dvornikov, P. A. Skripkina, T. A. Gaydina, E. V. Trushina

“…Due to the fact that subsequent traditional anti-acne algorithms of topical and oral treatment was not such effective, there was made a decision to use an alternative supporting external therapy, which did not have similar examples of usage previously. …”
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Severe COVID-19 in Third Trimester Pregnancy: Multidisciplinary Approach by Jerald Pelayo, Gabriella Pugliese, Grace Salacup, Eduardo Quintero, Adeeb Khalifeh, David Jaspan, Bhavna Sharma

“…The neonate was discharged on the 2nd day of life, while the patient was extubated on the 6th postpartum day and was discharged to acute inpatient rehabilitation facility on the 19th hospital day. …”
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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection by Muhammad Shafiq, J. Kavitha, Dhruva R. Rinku, N. K. Senthil Kumar, Kamal Poon, Amar Y. Jaffar, V. Saravanan

“…Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during gestation. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…The accurate prediction of the residual strength of defective pipelines is a critical prerequisite for ensuring the safe operation of oil and gas pipelines, and it holds significant implications for the pipeline’s remaining service life and preventive maintenance. Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
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SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS by Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

“…In the study discussed here, different machine learning (ML) algorithms were investigated to foresee construction delays, and these include Gaussian Naïve Bayes, Adaboost, Logistic Regression, Gradient Boosting (GB), Random Forest (RF), Decision Tree (DT) and Extreme Gradient Boosting (XGBoost). …”
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A Novel Tool for Biodiversity Studies: Earthworm Classification via NGS and Neural Networks by Tadeusz Malewski, Ewa Ropelewska, Andrzej Skwiercz, Anastasiia Lutsiuk, Anita Zapałowska

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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. The subtle changes in hearing often go unnoticed, presenting a challenge for early hearing loss detection. …”
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