Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis by Jingtai Ma, Jingtai Ma, Yiting Fang, Yiting Fang, Shiqi Li, Shiqi Li, Lilian Zeng, Siyi Chen, Zhifeng Li, Guiyuan Ji, Xingfen Yang, Wei Wu, Wei Wu

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Comparison of Deep Learning and Clinician Performance for Detecting Referable Glaucoma from Fundus Photographs in a Safety Net Population by Van Nguyen, MD, Sreenidhi Iyengar, Haroon Rasheed, MD, Galo Apolo, Zhiwei Li, Aniket Kumar, Hong Nguyen, Austin Bohner, MD, Kyle Bolo, MD, Rahul Dhodapkar, MD, Jiun Do, MD, PhD, Andrew T. Duong, MD, Jeffrey Gluckstein, MD, Kendra Hong, MD, Lucas L. Humayun, Alanna James, MD, Junhui Lee, MD, Kent Nguyen, OD, Brandon J. Wong, MD, Jose-Luis Ambite, PhD, Carl Kesselman, PhD, Lauren P. Daskivich, MD, Michael Pazzani, PhD, Benjamin Y. Xu, MD, PhD

“…Implementation of this algorithm in screening workflows could help reallocate resources and provide more reproducible and timely glaucoma care. …”
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Surrogate-assisted global and distributed local collaborative optimization algorithm for expensive constrained optimization problems by Xiangyong Liu, Zan Yang, Jiansheng Liu, Junxing Xiong, Jihui Huang, Shuiyuan Huang, Xuedong Fu

“…For global surrogate-assisted collaborative evolution phase, the global candidate set is generated through classification collaborative mutation operations to alleviate the pre-screening pressure of the surrogate model. For local surrogate-assisted phase, a distributed central region local exploration is designed to achieve intensively search for promising distributed local areas which are located by affinity propagation clustering and mathematical modeling. …”
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Artificial Intelligence With Neural Network Algorithms in Pediatric Astrocytoma Diagnosis: A Systematic Review by Floresya K. Farmawati, Della W.A. Nurwakhid, Tifani A. Pradhea, Rayyan Fitriasa, Hutami H. Arrahmi, Muhana F. Ilyas, Fadhilah T. Nur

“…The AI models exhibited performance levels comparable to or exceeding that of expert radiologists, with metrics such as tumor classification accuracy of 92% and high values of the area under the receiver operating characteristic curve.Conclusions: AI with neural network algorithms shows significant promise in enhancing accuracy of pediatric astrocytoma diagnosis. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Abstract Context Understanding protein-ligand interactions is fundamental to drug design, where optimizing docking parameter selection can potentially enhance computational efficiency and resource allocation in virtual screening. While numerous algorithms exist for protein-ligand docking, achieving an optimal balance between accuracy and computational speed remains challenging. …”
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An Automated Algorithm for Obstructive Sleep Apnea Detection Using a Wireless Abdomen-Worn Sensor by Thi Hang Dang, Seong-mun Kim, Min-seong Choi, Sung-nam Hwan, Hyung-ki Min, Franklin Bien

“…Wireless wearable devices have emerged as promising tools for OSA screening and follow-up. This study introduces a novel automated algorithm for detecting OSA using abdominal movement signals and acceleration data collected by a wireless abdomen-worn sensor (Soomirang). …”
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Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes—a multi-site natural experiment by Sarah Tonkin-Crine, Graham Cooke, Anthony C Gordon, Anthony Gordon, Shashank Patil, Runa Lazzarino, Andrew Brent, Kate Honeyford, Céire E Costelloe, Anne Kinderlerer, John Welch, Peter Ghazal, Claire Burnett, Alf Timney, Andrew Jonathan Brent, Cerie Costelloe, Pippa Goodman Ben Glampson

“…We evaluated the impact of sepsis screening tools on in-patient 30-day mortality across four multi-hospital NHS Trusts, each using a different algorithm for early detection of sepsis.Methods Using quasi-experimental methods, we investigated the impact of the screening tools. …”
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One scan, multiple insights: A review of AI-Driven biomarker imaging and composite measure detection in lung cancer screening by Saher Verma, Leander Maerkisch, Alberto Paderno, Leonard Gilberg, Bianca Teodorescu, Mathias Meyer

“…Through an extensive review of current literature sourced from PubMed, the review highlights advancements in AI-driven biomarker detection, evaluates the potential benefits of a broader diagnostic approach, and addresses challenges related to model standardization and clinical integration. AI-enhanced LDCT screening shows significant promise in augmenting routine screenings, potentially advancing early detection, comprehensive patient assessments, and overall disease management across multiple health conditions.…”
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Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

“…Data augmentation allows researchers to expand the dataset, providing a larger and more diverse set of examples for model training. …”
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Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

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Evaluation Algorithm of Ecological Energy-Saving Effect of Green Buildings Based on Gray Correlation Degree by Chongyu Wang

“…The environmental protection attribute and energy-saving level of green buildings cannot be described by the traditional evaluation model. In order to solve the above problems, a new ecological energy-saving effect evaluation algorithm of green buildings based on gray correlation degree is designed. …”
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Data Mining and Analysis of the Compatibility Law of Traditional Chinese Medicines Based on FP-Growth Algorithm by Shuchun Zhou

“…In terms of compatibility law of traditional Chinese antiviral prescriptions, this paper studied the compatibility law of traditional Chinese antiviral prescriptions based on the FP-growth algorithm and made exploratory research on the compatibility law information of 961 traditional classical antiviral prescriptions. …”
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Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study by Wiyada Quanchareonsap, Ngamjit Kasetsuwan, Usanee Reinprayoon, Yonrawee Piyacomn, Thitima Wungcharoen, Monthira Jermjutitham

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PhyIndBC: Development of a machine learning tool for screening of potential breast cancer inhibitors from phytochemicalsGitHub by Agneesh Pratim Das, Subhash M. Agarwal

“…Multiple ML techniques viz., k-nearest neighbor (KNN), random forest (RF), support vector machine (SVM), and extreme gradient boosting (XGB) were combined with various molecular fingerprints (MACCS and Morgan2) to develop multiple predictive models. Among these models, the RF algorithm coupled with the MACCS fingerprint emerged as the best performing model. …”
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Identification and Validation of NK Marker Genes in Ovarian Cancer by scRNA-seq Combined with WGCNA Algorithm by Xin He, Weiwei Feng

“…The LASSO-COX algorithm was employed to build risk models to predict prognosis. …”
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The Development of a Brief but Comprehensive Therapeutic Assessment Protocol for the Screening and Support of Youth in the Community to Address the Youth Mental Health Crisis by Margaret Danielle Weiss, Eleanor Castine Richards, Danta Bien-Aime, Taylor Witkowski, Peyton Williams, Katie E. Holmes, Dharma E. Cortes, Miriam C. Tepper, Philip S. Wang, Rajendra Aldis, Nicholas Carson, Benjamin Le Cook

“…Objective: The objective of this study was to explore the acceptability and feasibility of a therapeutic assessment protocol for the Screening and Support of Youth (SASY). SASY provides brief but comprehensive community-based screening and support for diverse youth in the community. …”
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MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. by Chao Wang, Quan Zou

“…To date, most tools are designed for model organisms, but only a handful of methods are suitable for predicting task in fungal species, and their performance still leaves much to be desired. …”
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The True Shortest Path of Obstacle Grid Graph Is Solved by SGP Vertex Extraction and Filtering Algorithm by Yijie Zhang, Jizhou Chen

“…Through various experiments, the shortest path length searched by the SGPVEFA proposed in this paper can be used to search for the real shortest path, and it also has advantages in comparison with recent new algorithms. With the increase in map scale and obstacle rate, the advantages of this path algorithm are more significant.…”
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In Silico Evaluation of Algorithm-Based Clinical Decision Support Systems: Protocol for a Scoping Review by Michael Dorosan, Ya-Lin Chen, Qingyuan Zhuang, Shao Wei Sean Lam

“…MethodsWe propose a scoping review protocol that follows an enhanced Arksey and O’Malley framework and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines to investigate the scope and research gaps in the in silico evaluation of algorithm-based CDS models—specifically CDS decision-making end points and objectives, evaluation metrics used, and simulation paradigms used to assess potential impacts. …”
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Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

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