Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…Objective: Bloodstream infections (BSIs) require rapid identification to initiate timely antimicrobial therapy, yet blood culture-the current diagnostic gold standard-suffers from delayed results and limited sensitivity. …”
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Principles of physical factor selection in the early postoperative period of breast cancer treatment: a randomized controlled study by Inna S. Evstigneeva

“…INTRODUCTION. Current models of onco-rehabilitation do not consider the patient’s functional impairment during combined treatment until the patient becomes incapacitated and the impairment develops into a chronic condition. …”
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Improved breast cancer risk prediction using chromosomal-scale length variation by Yasaman Fatapour, James P. Brody

“…We used machine learning algorithms to find a model that best differentiates the women with breast cancer from the women without breast cancer based on the set of 88 numbers that characterize each woman’s germline genome. …”
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Universal multilayer network embedding reveals a causal link between GABA neurotransmitter and cancer by Léo Pio-Lopez, Michael Levin

“…However, drug discovery in the context of complex phenotypes are hampered by the difficulties inherent in producing machine learning algorithms that can integrate molecular-genetic, biochemical, physiological, and other diverse datasets. …”
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Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays. by Ankit Srivastava, Qinlu Wang, Christina D Orrù, Manel Fernandez, Yaroslau Compta, Bernardino Ghetti, Gianluigi Zanusso, Wen-Quan Zou, Byron Caughey, Catherine A A Beauchemin

“…In some scenarios, analysis of the data using Poisson and midSIN algorithms provided more consistent and statistically significant discrimination of different seed concentrations. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This work paves the way for deploying high-accuracy, real-time scene flow algorithms in autonomous driving, advancing the field towards more responsive and safer autonomous systems.…”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…<b>Background/Objectives</b>: Obstructive sleep apnea (OSA) classification relies on polysomnography (PSG) results. Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. …”
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Outpatient diagnosis of endogenous intoxication in surgery by A. A. Solomakha, A. P. Vlasov, V. I. Gorbachenko

“…Statistical, neural network and algorithms with elements of fuzzy neural networks were used on a sample consisting of hematological parameters of 274 patients with chronic kidney disease and healthy ones based on 25 laboratory parameters. …”
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Research on Method for Intelligent Recognition of Deep-Sea Biological Images Based on PSVG-YOLOv8n by Dali Chen, Xianpeng Shi, Jichao Yang, Xiang Gao, Yugang Ren

“…Nonetheless, the inherent complexities of the deep-sea environment, the scarcity of available deep-sea organism samples, and the significant refraction and scattering effects of underwater light collectively impose formidable challenges on the current detection algorithms. To address these issues, we propose an advanced deep-sea biometric identification framework based on an enhanced YOLOv8n architecture, termed PSVG-YOLOv8n. …”
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Duck Egg Crack Detection Using an Adaptive CNN Ensemble with Multi-Light Channels and Image Processing by Vasutorn Chaowalittawin, Woranidtha Krungseanmuang, Posathip Sathaporn, Boonchana Purahong

“…However, duck eggs present a unique challenge due to their white eggshells, which make cracks difficult to detect visually. In current practice, human inspectors use standard white light for crack detection, and many researchers have focused primarily on improving detection algorithms without addressing lighting limitations. …”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…The paper concludes by emphasizing the transformative potential of deep learning in achieving automated, accurate, and efficient defect detection in wind turbine blades. Addressing current limitations through interdisciplinary research and innovative algorithms will pave the way for sustainable and cost-effective wind energy systems, ultimately contributing to the global transition toward renewable energy.…”
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The unwell patient with advanced chronic liver disease: when to use each score? by Oliver Moore, Wai-See Ma, Scott Read, Jacob George, Golo Ahlenstiel

“…Organ allocation for liver transplantation is also currently prioritised using the MELD score, with the MELD 3.0 reducing waitlist gender discrepancies. …”
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Comparing miR-16 and miR-1228 as an optimal endogenous control for quantification of circulating microRNAs in colorectal cancer patients by Chia-Lin Yang, Fu-Ming Tsai, Chuang-Wei Chen, Kuan-Hong Hsiao, Jia-Hui Chen, Woei-Yau Kao

“…They are emerging candidates for noninvasive molecular biomarkers of cancer and other diseases. However, current translational researches have been limited by the lack of consensus on the optimal endogenous control of circulating miRNAs quantitation. …”
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EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

“…Unfortunately, optimization of diagnostic algorithms and wide implementation of instrumental diagnostics (ultrasound examination, computed tomography, fiber endoscopy) do not improve the situation. …”
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Intelligent fault diagnosis of shearer based on simplified interval kernel global-local feature fusion by Ning LI, Hua DING, Xiaochun SUN, Zeping LIU, Guoshu PU

“…To accurately monitor the health state of shearer, based on easily available data such as current, temperature and flow under normal state of shearer, the global and local characteristics of the dataset are comprehensively considered to avoid the loss of structural information. …”
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Assessment of copeptin and obestatin levels in coronary artery disease patients by Saraa Ali, Fatma F. Abdel Hamid, Samia Hussein, Shaimaa Wageeh, Doaa M. Ibrahim

“…Abstract Background Acute coronary syndrome (ACS) is classified into acute myocardial infarction (AMI), and unstable angina (UA). They are currently assessed clinically through myocardial enzymes, electrocardiography, risk score algorithms, and angiography. …”
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The Northern Giona Fault Zone, a Major Active Structure Through Central Greece by Leonidas Gouliotis, Dimitrios Papanikolaou

“…Inversion of fault-slip data has shown a mean slip vector of 45°, N004°E, which aligns with the current regional extensional deformation of the area, as confirmed by focal mechanism solutions. …”
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Using de novo assembly to identify structural variation of eight complex immune system gene regions. by Jia-Yuan Zhang, Hannah Roberts, David S C Flores, Antony J Cutler, Andrew C Brown, Justin P Whalley, Olga Mielczarek, David Buck, Helen Lockstone, Barbara Xella, Karen Oliver, Craig Corton, Emma Betteridge, Rachael Bashford-Rogers, Julian C Knight, John A Todd, Gavin Band

“…Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. …”
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Deep‐HH: A deep learning‐based high school student hidden hunger risk prediction system by Yang Yang, Zheng Zhang, Huake Cao, Yuchen Zhang, Minao Wang, Ning Zhang

“…Abstract Background Hidden hunger (HH) refers to the deficiency of certain micronutrients. Current research suggests that approximately 70% of chronic diseases are linked to HH, which significantly affects public health. …”
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Sort & Slice: a simple and superior alternative to hash-based folding for extended-connectivity fingerprints by Markus Dablander, Thierry Hanser, Renaud Lambiotte, Garrett M. Morris

“…Abstract Extended-connectivity fingerprints (ECFPs) are a ubiquitous tool in current cheminformatics and molecular machine learning, and one of the most prevalent molecular feature extraction techniques used for chemical prediction. …”
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