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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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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Socially excluded employees prefer algorithmic evaluation to human assessment: The moderating role of an interdependent culture by Yoko Sugitani, Taku Togawa, Kosuke Motoki

“…Further, this effect was mediated by perceived fairness of AI assessment, and more evident in an interdependent (but not independent) self-construal culture. …”
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Denoising Algorithm for High-Resolution and Large-Range Phase-Sensitive SPR Imaging Based on PFA by Zihang Pu, Xuelin Wang, Wanwan Chen, Zhexian Liu, Peng Wang

“…The algorithm demonstrates 57% instrumental noise reduction and achieves 1.51 × 10⁻⁶ RIU resolution (1.333–1.393 RIU range). …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

“…On November 6, 2022, about 196 scholarly articles were downloaded from three digital libraries: Science Direct (38), ACM Digital Library (72), IEEE Xplore (51), and 35 from the Google Scholar search engine. After screening and eligibility checking, 28 scholarly articles were selected and analysed through content analysis in terms of the most commonly used algorithms, the year of publication, the study purposes, and the accuracy performance metrics. …”
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Cystic Fibrosis Newborn Screening: A Systematic Review-Driven Consensus Guideline from the United States Cystic Fibrosis Foundation by Meghan E. McGarry, Karen S. Raraigh, Philip Farrell, Faith Shropshire, Karey Padding, Cambrey White, M. Christine Dorley, Steven Hicks, Clement L. Ren, Kathryn Tullis, Debra Freedenberg, Q. Eileen Wafford, Sarah E. Hempstead, Marissa A. Taylor, Albert Faro, Marci K. Sontag, Susanna A. McColley

“…Systematic reviews were used to develop seven recommendations for newborn screening program practices to improve timeliness, sensitivity, and equity in diagnosing infants with CF: (1) The CF Foundation recommends the use of a floating immunoreactive trypsinogen (IRT) cutoff over a fixed IRT cutoff; (2) The CF Foundation recommends using a very high IRT referral strategy in CF newborn screening programs whose variant panel does not include all CF-causing variants in CFTR2 or does not have a variant panel that achieves at least 95% sensitivity in all ancestral groups within the state; (3) The CF Foundation recommends that CF newborn screening algorithms should not limit <i>CFTR</i> variant detection to the F508del variant or variants included in the American College of Medical Genetics-23 panel; (4) The CF Foundation recommends that CF newborn screening programs screen for all CF-causing <i>CFTR</i> variants in CFTR2; (5) The CF Foundation recommends conducting <i>CFTR</i> variant screening twice weekly or more frequently as resources allow; (6) The CF Foundation recommends the inclusion of a <i>CFTR</i> sequencing tier following IRT and <i>CFTR</i> variant panel testing to improve the specificity and positive predictive value of CF newborn screening; (7) The CF Foundation recommends that both the primary care provider and the CF specialist be notified of abnormal newborn screening results. …”
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Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence by Marcela Arrivillaga, Paula C. Bermúdez, Juan Pablo García-Cifuentes, Hernán Darío Vargas-Cardona, Daniela Neira, Maria del Mar Torres, Mérida Rodríguez-López, Daniela Morales, Bleider Arizala

“…Additionally, we developed AI algorithms using the Inception V3 network, optimized with Transfer Learning and Fine Tuning, for cervical image classification and offline-operating software that guides the physician through the examination and provides a risk assessment for cervical cancer. …”
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LPCF-YOLO: A YOLO-Based Lightweight Algorithm for Pedestrian Anomaly Detection with Parallel Cross-Fusion by Peiyi Jia, Hu Sheng, Shijie Jia

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Automated detection of hard exudates in retinal fundus images for diabetic retinopathy screening using textural-based radon transform and morphology reconstruction by Esmat Ramezanzadeh, Naser Shoeibi, Akram Feizabadi, Touka Banaee, Mohammad Hossein Bahreyni Tussi, Meysam Tavakoli

“…Background: Diabetic retinopathy (DR) screening requires accurate detection of hard exudates (HEs) in retinal images. …”
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Algorithmic indexing in MEDLINE frequently overlooks important concepts and may compromise literature search results by Alexandre Amar-Zifkin, Taline Ekmekjian, Virginie Paquet, Tara Landry

“…Three main issues with algorithmically-indexed records were identified: 1) inappropriate MeSH assigned due to acronyms, evocative language, exclusions of populations, or related records; 2) concepts represented by more general MeSH while a more precise MeSH is available; and 3) a significant concept not represented in the indexing at all. …”
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