Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle by Jawoon Gu, Dongwoo Kim, Chulmin Jun, Seungwoo Son

“…High-resolution thermal imagery captured by unmanned aerial vehicles (UAVs) and interpretable machine learning (ML) techniques were used to model and analyze thermal patterns at the microscale. …”
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Longitudinal image-based prediction of surgical intervention in infants with hydronephrosis using deep learning: Is a single ultrasound enough? by Adree Khondker, Stanley Bryan Z Hua, Jethro C C Kwong, Kunj Sheth, Daniel Alvarez, Kyla N Velaer, John Weaver, Alice Xiang, Gregory E Tasian, Armando J Lorenzo, Anna Goldenberg, Mandy Rickard, Lauren Erdman

“…The potential of deep learning to predict renal obstruction using kidney ultrasound images has been demonstrated. …”
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Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms by Meijuan Peng, Chen Jiang, Ziyu Dai, Bin Xie, Qiong Chen, Jianing Lin

“…Abstract Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated with COPD and its immune microenvironment. …”
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A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning by Brian Sang, Haoran Wen, Greg Junek, Wendy Neveu, Lorenzo Di Francesco, Justin Romberg, Farrokh Ayazi

“…Abstract Physicians evaluate a patient’s respiratory health during a physical examination by visual assessment of the work of breathing (WoB) to determine respiratory stability, and by detecting abnormal lung sounds via lung auscultation using a stethoscope to identify common pathological lung diseases, such as chronic obstructive pulmonary disease (COPD) and pneumonia. …”
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Potential for artificial intelligence in medicine and its application to male infertility by Hideyuki Kobayashi

“…Abstract Background The third AI boom, which began in 2010, has been characterized by the rapid evolution and diversification of AI and marked by the development of key technologies such as machine learning and deep learning. AI is revolutionizing the medical field, enhancing diagnostic accuracy, surgical outcomes, and drug production. …”
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Adaptive Generation Method for Small Volume Easy Fabrication Freeform Unobscured Three-Mirror Systems Based on Machine Learning by Yiwei Sun, Yangjie Wei, Ji Zhao

“…Freeform unobscured multiple-mirror systems have been widely applied in high-precision optical fields due to their high imaging quality and no chromatic aberration and central obstruction. However, how to design a freeform unobscured multiple-mirror system with small system volume, imaging quality, and low manufacturing difficulty is challenging. …”
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Key RNA-binding proteins in renal fibrosis: a comprehensive bioinformatics and machine learning framework for diagnostic and therapeutic insights by Jie Chen, Binghan Zhang, Qixuan Huang, Ronghua Fang, Ziyu Ren, Dongfang Liu

“…The integration of bioinformatics and machine learning emphasizes their translational potential in kidney care.…”
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Machine learning-based diagnostic model for neonatal intestinal diseases in multiple centres: a cross-sectional study protocol by Xiang Guo, Jing Shi, Yue Han, Qi Zhao, Jun Tang, Tao Xiong, Yi Yang, Jin Zhang, Qian Gao, Ling He

“…This study aims to develop an machine learning-based diagnostic model for neonatal intestinal diseases using BS analysis and to compare its diagnostic accuracy with that of manual clinical assessment.Methods and analysis This diagnostic study employs a cross-sectional design. …”
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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

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HAP-COVID: Hybrid Model Integrating Machine Learning and Neutrosophic Statistics to Estimate Mortality Risk in COVID-19 Comorbid Patients by Daniel Iturburu-Salvador, Lorenzo Cevallos-Torres, Rosangela Caicedo-Quiroz, Irma Naranjo-Peña, Rosa Hernández-Magallanes, Rosa Gonzáles-Quiñones

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Single Cell Transcriptomics Genomics Based on Machine Learning Algorithm: Constructing and Validating Neutrophil Extracellular Trap Gene Model in COPD by Yu J, Xiao T, Pan Y, He Y, Tan J

“…Machine learning algorithms were applied to construct models A and B, specific to smoking and non-smoking COPD patients, respectively.Results: Through single-cell cluster analysis, 165 neutrophil characteristic genes in COPD group were successfully identified. …”
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Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network accuracy in Sweden by William Lidberg

“…Study region: Sweden, a mostly forested country with many small forest roads obstructing topographical modelling of shallow groundwater and streams. …”
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Designing Synchronous Online Learning and Teaching Lab: An Online Professional Development Program to Foster the Technical and Social Competences of Synchronous Online Teachers by Maaike Grammens, Fien De Smedt, Bram De Wever

“…A detailed overview of the online PD design is offered, encompassing the underlying theoretical and empirical foundations, macro-level design principles, and micro-level instructional and learning activities. More particularly, three key design principles guided the online PD development process: focused observation of SOT, providing and receiving feedback, and stimulating the transfer of learning. …”
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Comprehensive bioinformatics analysis identifies metabolic and immune-related diagnostic biomarkers shared between diabetes and COPD using multi-omics and machine learning by Qianqian Liang, Yide Wang, Zheng Li, Zheng Li, Zheng Li, Zheng Li

“…BackgroundDiabetes and chronic obstructive pulmonary disease (COPD) are prominent global health challenges, each imposing significant burdens on affected individuals, healthcare systems, and society. …”
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Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study by Tiansheng Xia, Kaiyu Han

“…Abstract Background Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. …”
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Enhanced machine learning predictive modeling for delirium in elderly ICU patients with COPD and respiratory failure: A retrospective study based on MIMIC-IV. by Zong-Bi Wu, You-Li Jiang, Shuai-Shuai Li, Ao Li

“…<h4>Methods</h4>Data for the machine learning model were obtained from the MIMIC-IV database. …”
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Enhancing occluded and standard bird object recognition using fuzzy-based ensembled computer vision approach with convolutional neural network by L. Richard, G. H. Dhruthi, M. Ashwin Kumar, Anoushka Ghosh, R. Arumuga Arun, N. Priyanka

“…Our ensemble method adaptively allocates model weights based on feature contributions found using fuzzy logic, in contrast to existing methods that have trouble with obstructed images. Since, every CNN model candidate in the suggested fuzzy-based ensemble learning showed excellent classification performance, the proposed fuzzy-based ensemble approach achieving 98.73% accuracy, a 98.75% F1-score for standard images, and 95.78% accuracy, and a 95.1% F1-score for occluded images, the results indicating performance improvements of 2% for standard and 9% for occluded bird images over the methods used in existing research work. …”
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A novel interpretable deep learning model for diagnosis in emergency department dyspnoea patients based on complete data from an entire health care system. by Ellen T Heyman, Awais Ashfaq, Ulf Ekelund, Mattias Ohlsson, Jonas Björk, Ardavan M Khoshnood, Markus Lingman

“…We aimed to design a diagnostic decision support which classifies dyspnoeic ED visits into acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), pneumonia and "other diagnoses" by using deep learning and complete, unselected data from an entire regional health care system.…”
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Supporting long-term condition management: a workflow framework for the co-development and operationalization of machine learning models using electronic health record data insight... by Shane Burns, Andrew Cushing, Anna Taylor, David J. Lowe, Christopher Carlin

“…The prevalence of long-term conditions such as cardiovascular disease, chronic obstructive pulmonary disease (COPD), asthma, and diabetes mellitus is rising. …”
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Innovación en sueño by Laura Vigil, Toni Zapata, Andrea Grau, Marta Bonet, Montserrat Montaña, María Piñar

“…Abstract: Advances in sleep medicine have driven significant improvements in the diagnosis and treatment of sleep disorders such as obstructive sleep apnea (OSA). This disorder affects one billion people worldwide and traditionally, diagnosis is based on polysomnography (PSG), a laborious method that requires specialized personnel. …”
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