Predicting chronic kidney disease progression using small pathology datasets and explainable machine learning models by Sandeep Reddy, Supriya Roy, Kay Weng Choy, Sourav Sharma, Karen M Dwyer, Chaitanya Manapragada, Zane Miller, Joy Cheon, Bahareh Nakisa

“…Supervised classification modelling techniques included decision tree and random forest algorithms selected for interpretability. Internal validation on an Australian tertiary centre cohort (n = 706; 353 with kidney failure and 353 without) achieved exceptional predictive accuracy. …”
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Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimizatio... by Hanxuan Wang, Raman Kumar, Raman Kumar, Ashutosh Pattanaik, Rajender Kumar, Rajender Kumar, Ali Saeed Owayez Khawaf Aljaberi, Mayada Ahmed Abass

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Teens and opioids postsurgery (TOPS): protocol for a prospective observational study describing associations between sleep deficiency and opioid use following outpatient surgery in... by Tonya Palermo, Jennifer A Rabbitts, Cornelius B Groenewald, Rebecca L Flack, Sophia L Kreider

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Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery by Andrii Zaiats, T. Trevor Caughlin, Jennyffer Cruz, David S. Pilliod, Megan E. Cattau, Rongsong Liu, Richard Rachman, Maisha Maliha, Donna Delparte, John D. J. Clare

“…Abstract Estimating and monitoring plant population size is fundamental for ecological research, as well as conservation and restoration programs. …”
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Identification and validation of neutrophil-related biomarkers in acute-on-chronic liver failure by Wei Lin, Yongping Chen, Yongping Chen, Mingqin Lu, Cheng Peng, Cheng Peng, Xiang Chen, Xiang Chen, Xiaoqin Liu, Yunyun Wang, Yunyun Wang

“…However, additional research is required to substantiate the effects of these key genes and therapeutic agents on ACLF.…”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Objective: To provide a comprehensive review on the existing research and evidence regarding artificial intelligence (AI) applications in the assessment and management of urinary stone disease. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

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Machine learning predictive model for aspiration risk in early enteral nutrition patients with severe acute pancreatitis by Bo Zhang, Huanqing Xu, Qigui Xiao, Wanzhen Wei, Yifei Ma, Xinlong Chen, Jingtao Gu, Jiaoqiong Zhang, Lan Lang, Qingyong Ma, Liang Han

“…Subsequently, we used six machine learning algorithms and the model was validated by the area under the curve. …”
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Comprehensive analysis of regulatory B Cell related genes in prognosis and therapeutic response in lung adenocarcinoma by Liangyu Zhang, Liangyu Zhang, Jianshen Zeng, Jianshen Zeng, Xun Zhang, Xun Zhang, Menglong Zhang, Menglong Zhang, Yilin Lin, Yilin Lin, Fancai Lai, Fancai Lai

“…Differentially expressed genes between the two clusters were then used to construct the BREGI using 32 algorithms, including traditional regression, machine learning, deep learning, and 274 different combinations. …”
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Context guided transformer enhanced YOLOv8 for accurate juvenile abalone detection and counting by Dapeng Cheng, Ji Ruan, Xinhao Li, Feng Zhao, Shoudu Zhang, Guofan Zhang, Fucun Wu

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Beyond the Scalpel: Assessing ChatGPT's potential as an auxiliary intelligent virtual assistant in oral surgery by Ana Suárez, Jaime Jiménez, María Llorente de Pedro, Cristina Andreu-Vázquez, Víctor Díaz-Flores García, Margarita Gómez Sánchez, Yolanda Freire

“…Noteworthy advances in AI algorithms and large language models (LLM) have led to the development of natural generative language (NGL) systems such as ChatGPT. …”
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Machine Learning-Driven Transcriptome Analysis of Keratoconus for Predictive Biomarker Identification by Shao-Hsuan Chang, Lung-Kun Yeh, Kuo-Hsuan Hung, Yen-Jung Chiu, Chia-Hsun Hsieh, Chung-Pei Ma

“…Our findings provide a novel research platform for the evaluation of keratoconus using machine learning-based approaches, offering valuable insights into its pathogenesis and potential therapeutic targets.…”
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Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers by Wentong Li, Yiyi Zhang, Chuanhong Li, Mingyang Jiang, Dong Wang, Luomeng Chao, Luomeng Chao, Luomeng Chao, Yuxia Yang

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Prominent events in the development of a simultaneous multidiagnostic system with synthetic peptides by Oscar Noya, Henry Bermúdez, Diana Pachón, Belkisyolé Alarcón de Noya, Diana Ortiz-Princz, Flor Helene Pujol, Sandra Losada

“…Simultaneous multidiagnostic methods are desirable; however, they are mostly expensive and inaccessible to the populations of the region. The aim of our research was to produce synthetic peptides of the most important pathogens that can be used in a simultaneous multidiagnostic technique. …”
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Development of a hoRizontal data intEgration classifier for NOn-invasive early diAgnosis of breasT cancEr: the RENOVATE study protocol by Gabriele Zoppoli, Alberto Ballestrero, Valerio Gaetano Vellone, Piero Fregatti, Francesco Ravera, Gabriella Cirmena, Martina Dameri, Maurizio Gallo, Daniele Friedman, Massimo Calabrese, Alberto Tagliafico, Lorenzo Ferrando

“…These analyses will be combined with radiomic variables extracted with freeware algorithms applied to cases and matched controls for which digital mammography is available. …”
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Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study by Yejing Zhao, Yejing Zhao, Xiang Wang, Jie Zhang, Yanyan Zhao, Yi Li, Ji Shen, Ying Yuan, Jing Li

“…The contemporary consensus firmly emphasizes the urgent need to reorient research efforts toward the early detection of preclinical Alzheimer’s disease (AD) or mild cognitive impairment (MCI). …”
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Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning by Leeran Talker, Cihan Dogan, Daniel Neville, Rui Hen Lim, Henry Broomfield, Gabriel Lambert, Ahmed Selim, Thomas Brown, Laura Wiffen, Julian Carter, Helen F. Ashdown, Gail Hayward, Elango Vijaykumar, Scott T. Weiss, Anoop Chauhan, Ameera X. Patel

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Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

“…In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.ConclusionThis research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. …”
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Comprehensive characterization of T cell subtypes in lung adenocarcinoma: Prognostic, predictive, and therapeutic implications by Shiquan Liu, Hao Sun, Tianye Song, Ce Liang, Lele Deng, Haiyong Zhu, Fangchao Zhao, Shujun Li

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Preoxygenation in difficult airway management: high-flow oxygenation by nasal cannula versus face mask (the PREOPTIDAM study). Protocol for a single-centre randomised study by Samir Jaber, Karim Asehnoune, Fanny Feuillet, Mickael Vourc’h, Donatien Huard, Gabrielle Baud, Arthur Guichoux, Marielle Surbled, Melanie Tissot, Anne Chiffoleau, Christophe Guitton

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