Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease by Ivar R. deVries, Judith O. E. H. vanLaar, Marieke B. van der Hout‐van der Jagt, Sally‐Ann B. Clur, Rik Vullings

“…More research is required to improve performance and determine the benefits to clinical practice.…”
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Diabetes and Cataracts Development—Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study by Adriana Ivanescu, Simona Popescu, Adina Braha, Bogdan Timar, Teodora Sorescu, Sandra Lazar, Romulus Timar, Laura Gaita

“…<i>Conclusions:</i> These findings suggest that diabetes may impact the type of cataract that develops, with CC being notably more prevalent in diabetic patients. This has important implications for screening and management strategies for cataract formation in diabetic populations.…”
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Automated interpretation of influenza hemagglutination inhibition (HAI) assays: Is plate tilting necessary? by Garrett Wilson, Zhiping Ye, Hang Xie, Steven Vahl, Erica Dawson, Kathy Rowlen

“…In a side-by-side comparison study performed during FDA's biannual serological screening process for influenza viruses, titer calls for more than 2200 serum samples were made by the Cypher One automated hemagglutination analyzer without tilting and by an expert human with tilting. …”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Conventional software such as Turnitin and iThenticate have come a long way, using deep learning algorithms to identify more evolved instances of academic fraud, including paraphrasing plagiarism and AI-generated content. …”
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Diagnosing cystic fibrosis in low- and middle-income countries: challenges and strategies by Michèle Fuhrer, Marco Zampoli, Hugues Abriel

“…Recent evidence indicates that Cystic Fibrosis is more common than initially thought and is likely underreported in low- and middle-income countries. …”
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Comparative Analysis of Osteoarthritis Therapeutics: A Justification for Harnessing Retrospective Strategies via an Inverted Pyramid Model Approach by Quinn T. Ehlen, Jacob Jahn, Ryan C. Rizk, Thomas M. Best

“…In comparison to the prospective approach, the retrospective strategy is likely more cost-effective, more widely applicable, and does not necessitate thorough and invasive genetic screening. …”
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Chinese AI tool ERNIE Bot Textual Exploration of False Information by Fu Yue

“…These countermeasures can not only enhance the detection ability of AI, but also give full play to human judgement in information screening, forming a more effective disinformation prevention mechanism. …”
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Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology. by Yuxi Long, Bruce R Donald

“…Compared to current binding affinity prediction algorithms, PATH+ shows similar or better accuracy and is more generalizable across orthogonal datasets. …”
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Effectiveness of mindfulness-based therapy, stress reduction in hypertension and prehypertension: a systematic review by D. I. Nozdrachev, M. N. Solovieva, K. A. Zamyatin

“…The systematic review was prepared according to the PRISMA algorithm with minor modifications. The search algorithm included articles in Russian and English, indexed in the Pubmed/MEDLINE and Cochrane Library databases. …”
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RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks. by Souvik Seal, Qunhua Li, Elle Butler Basner, Laura M Saba, Katerina Kechris

“…In RCFGL, we incorporate the condition specificity into another popular model for joint network estimation, known as fused multiple graphical lasso (FMGL). We use a more efficient algorithm in the iterative steps compared to CFGL, enabling faster computation with complexity of O(p2K) and making it easily generalizable for more than three conditions. …”
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Keypoint Detection Based on Curvature Grouping and Adaptive Sampling by Bifu Li, Yu Cheng, Weitong Li

“…In the keypoint detection algorithm, the farthest point sampling methods and random sampling methods are usually used to select candidate points, then keypoints are screened out from the neighborhood of the candidate points. …”
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Advancements in Machine Learning (ML): Transforming the Future of Blood Cancer Detection and Outcome Prediction by Wiebke Rösler, Michael Roiss, Corinne Widmer

“…The diagnosis and treatment of hematologic malignancies are becoming more and more complex. Growing knowledge of pathophysiology, diagnostic methods and, last but not least, treatment options offer many opportunities for patients, but integrating the growing amount of knowledge into daily practice can be challenging. …”
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Artificial Intelligence Powered Automated and Early Diagnosis of Acute Lymphoblastic Leukemia Cancer in Histopathological Images: A Robust SqueezeNet-Enhanced Machine Learning Fram... by Vineet Mehan

“…The growing prevalence of acute lymphoblastic leukemia cancer worldwide underlines the critical need for early and more precise detection to counter this deadly disease. …”
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Principles of effective out-patient diagnostics of diffuse liver diseases by Komova A. G., M. V. Mayevskaya, V. T. Ivashkin

“…Abnormal liver functional tests were revealed in 30,6% of industrial city inhabitants — in 1461 of 4768 cases (232 patients were excluded from the study due to partial data loss), significantly more frequently in men in comparison to women, i.e. 49,7 and 25,5% respectively (p&lt;0,001). …”
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Development of a high-performing, cost-effective and inclusive Afrocentric predictive model for stroke: a meta-analysis approach  by M Nweke, P Oyirinnaya, P Nwoha, SB Mitha, N Mshunqane, N Govender, M Ukwuoma, SC Ibeneme

“…Results More than 50% of the eligible studies examined both ischemic and hemorrhagic stroke. …”
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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…Omics-based biomarkers, like metabolomics, can make early diagnosis much more accurate, make tracking the disease’s progression more accurate, and help make personalized treatment plans that are tailored to each tumor’s specific molecular profile. …”
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A beginner’s approach to deep learning applied to VS and MD techniques by Stijn D’Hondt, José Oramas, Hans De Winter

“…However, both VS and MD come with their own limitations and methodological difficulties, from hardware limitations to restrictions in algorithmic capabilities. One solution to overcoming these difficulties lies in the field of machine learning (ML), and more specifically deep learning (DL). …”
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Iterative phase contrast CT reconstruction with novel tomographic operator and data-driven prior. by Stefano van Gogh, Subhadip Mukherjee, Jinqiu Xu, Zhentian Wang, Michał Rawlik, Zsuzsanna Varga, Rima Alaifari, Carola-Bibiane Schönlieb, Marco Stampanoni

“…Moreover, the highly ill-conditioned differential nature of the GI-CT forward operator renders the inversion from corrupted data even more cumbersome. In this paper, we propose a novel regularized iterative reconstruction algorithm with an improved tomographic operator and a powerful data-driven regularizer to tackle this challenging inverse problem. …”
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Cost-effectiveness analysis of best management practices for non-point source pollution in watersheds: A review by CHANG Jian, YU Jie, WANG Fei’er, ZHENG Siyuan

“…However, economic cost has been an important factor for screening the best management practice. Taking economic feasibility into consideration, the implementation of BMPs would be more practical and resource- saving, which can effectively alleviate the contradiction between economic development and environmental protection in basin management. …”
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Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria. by Tushar Garg, Stephen John, Suraj Abdulkarim, Adamu D Ahmed, Beatrice Kirubi, Md Toufiq Rahman, Emperor Ubochioma, Jacob Creswell

“…We provide implementation cost and cost-effectiveness estimates of different screening algorithms using symptoms, CXR and AI in Nigeria. …”
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