A Novel Approach for Maize Straw Type Recognition Based on UAV Imagery Integrating Height, Shape, and Spectral Information by Xin Liu, Huili Gong, Lin Guo, Xiaohe Gu, Jingping Zhou

“…Accurately determining the distribution and quantity of maize straw types is of great significance for evaluating the effectiveness of conservation tillage, precisely estimating straw resources, and predicting the risk of straw burning. …”
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Artificial Intelligence-Based Prediction of Bloodstream Infections Using Standard Hematological and Biochemical Markers by Ferhat DEMİRCİ, Murat AKŞİT, Aylin DEMİRCİ

“…Basophil count, while ranked highest by SHAP, showed low sensitivity, highlighting the difference between algorithmic weight and bedside utility. …”
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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

“…The pain syndrome (VAS), the difference in the circumference of the upper extremities (cm), muscle strength according to the Medical Research Council, the volume of movements in the shoulder joints, postoperative sutures according to the POSAS scale, daily volume of lymphorrhea, peripheral blood flow and life quality according to the SF-36 questionnaire were evaluated. …”
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Breast thermography: a systematic review and meta-analysis by Ane Goñi-Arana, Jorge Pérez-Martín, Francisco Javier Díez

“…However, advances in infrared technology and image processing algorithms in the twenty-first century led to a renewed interest in thermography. …”
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Dynamics of quality of life of head and neck cancer patients after treatment. Clinical significance by A. V. Karpenko, R. R. Sibgatullin, A. A. Boyko, M. G. Kostova, O. M. Nikolayeva, E. M. Trunin

“…The study objective is to evaluate the quality of life as one of the main parameters that determines the effectiveness of treatment of patients with head and neck squamous cell carcinoma.Materials and methods. …”
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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

“…They are currently assessed clinically through myocardial enzymes, electrocardiography, risk score algorithms, and angiography. It is important to find a suitable marker to differentiate them from other causes of chest pain. …”
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GenAI exceeds clinical experts in predicting acute kidney injury following paediatric cardiopulmonary bypass by Mansour Sharabiani, Alireza Mahani, Alex Bottle, Yadav Srinivasan, Richard Issitt, Serban Stoica

“…AKI could be a serious complication in paediatric CPB and its accurate prediction can significantly improve patient outcomes by enabling timely interventions. We evaluate various text embedding algorithms such as Doc2Vec, top-performing sentence transformers on Hugging Face, and commercial LLMs from Google and OpenAI. …”
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YouTube and Bilibili as sources of information on oral cancer: cross-sectional content analysis study by Qilei zhang, Zhe Li, Huiping Zhang, Ling Han, Shugang Zhao, Siyu Jia

“…Abstract This study aims to evaluate the informational quality of oral cancer-related videos on YouTube and Bilibili. …”
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Automated classification of stress and relaxation responses in major depressive disorder, panic disorder, and healthy participants via heart rate variability by Sangwon Byun, Ah Young Kim, Min-Sup Shin, Hong Jin Jeon, Hong Jin Jeon, Chul-Hyun Cho, Chul-Hyun Cho

“…This study evaluated the feasibility of using machine-learning algorithms to detect stress automatically in MDD and PD patients, as well as healthy controls (HCs), based on HRV features.MethodsThe study included 147 participants (MDD: 41, PD: 47, HC: 59) who visited the laboratory up to five times over 12 weeks. …”
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The State of Artificial Intelligence and its Prospects in Pakistan's Medical Sector by Rohail Akhtar Habib, Yumna Sattar Khan

“…Predictive analytics using machine learning algorithms has become more popular in Pakistani healthcare. …”
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EEG microstate analysis in children with prolonged disorders of consciousness by Yi Zhang, Zhichong Hui, Yuwei Su, Weihang Qi, Guangyu Zhang, Liang Zhou, Jiamei Zhang, Kaili Shi, Yonghui Yang, Lei Yang, Gongxun Chen, Sansong Li, Mingmei Wang, Dengna Zhu

“…Support vector machine (SVM) models were trained using combined temporal and spatial microstate features, optimized via grid search and random search algorithms. Model performance was evaluated using standard metrics, and features were ranked by permutation importance. …”
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River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model by Khabat Khosravi, Salim Heddam, Changhyun Jun, Sayed M. Bateni, Dongkyun Kim, Essam Heggy

“…Each model is trained and evaluated at one station and validated at the second station to assess transferability and generalization capability. …”
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Retrotransposon methylation profiles and survival in Black women with high-grade serous ovarian carcinoma by Christelle Colin-Leitzinger, Katherine A. Lawson-Michod, Courtney E. Johnson, Irma M. Vlasac, Sean Yoder, Tania Mesa, Dana Roeber, Chad Huff, Michelle A. T. Hildebrandt, Kristin Haller, Anthony J. Alberg, Elisa V. Bandera, Melissa Bondy, Michele L. Cote, Theresa Hastert, Edward S. Peters, Paul D. Terry, Andrew B. Lawson, Andrew Berchuck, Brooke L. Fridley, Jing-Yi Chern, Jennifer A. Doherty, Jeffrey R. Marks, Joellen M. Schildkraut, Brock C. Christensen, Lucas A. Salas, Lauren C. Peres

“…Methods Methylation levels of LTR, LINE-1, and Alu (type of SINE) in 200 HGSOC tumors were predicted using a random forest approach and clustered using multiple consensus algorithms. Associations between RE methylation clusters and survival were evaluated using Cox proportional hazard regression, adjusting for age, stage, and debulking status. …”
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Combined endodontic treatment: microbiological aspects by using scanning electronical microscopy by V. N. Tsarev, A. V. Mitronin, M. S. Podporin, D. A. Ostanina, E. V. Ippolitov, V. A. Mitronin

“…To determine possible alternative algorithms for root canal disinfection through the combined use of chemical and physiotherapeutic irrigation techniques under in vitro conditions.Materials and methods. …”
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Distribution of age at natural menopause, age at menarche, menstrual cycle length, height and BMI in BRCA1 and BRCA2 pathogenic variant carriers and non-carriers: results from EMBR... by Nasim Mavaddat, Debra Frost, Emily Zhao, Daniel R. Barnes, Munaza Ahmed, Julian Barwell, Angela F. Brady, Paul Brennan, Hector Conti, Jackie Cook, Harriet Copeland, Rosemarie Davidson, Alan Donaldson, Emma Douglas, David Gallagher, Rachel Hart, Louise Izatt, Zoe Kemp, Fiona Lalloo, Zosia Miedzybrodzka, Patrick J. Morrison, Jennie E. Murray, Alex Murray, Hannah Musgrave, Claire Searle, Lucy Side, Katie Snape, Vishakha Tripathi, Lisa Walker, Stephanie Archer, D. Gareth Evans, Marc Tischkowitz, Antonis C. Antoniou, Douglas F. Easton

“…The distributions of AAM, menstrual cycle length and BMI were similar between PV carriers and non-carriers, but BRCA1 PV carriers were slightly taller on average than non-carriers (0.5 cm difference, p = 0.003). Conclusion Information on the distribution of cancer risk factors in PV carriers is needed for incorporating these factors into multifactorial cancer risk prediction algorithms. …”
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A multidimensional assessment of adverse events associated with paliperidone palmitate: a real-world pharmacovigilance study using the FAERS and JADER databases by Siyu Lou, Zhiwei Cui, Yingyong Ou, Junyou Chen, Linmei Zhou, Ruizhen Zhao, Chengyu Zhu, Li Wang, Zhu Wu, Fan Zou

“…Utilizing disproportionality analyses such as the reporting odds ratios (ROR), proportional reporting ratios (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item Poisson shrinkage (MGPS), significant associations between ADEs and paliperidone palmitate were evaluated. Results A total of 27,672 ADE reports related to paliperidone palmitate were identified in FAERS, with 285 significantly disproportionate preferred terms (PTs) identified by all four algorithms. …”
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Comparative assessment of line probe assays and targeted next-generation sequencing in drug-resistant tuberculosis diagnosisResearch in context by Giovanna Carpi, Marva Seifert, Andres De la Rossa, Swapna Uplekar, Camilla Rodrigues, Nestani Tukvadze, Shaheed V. Omar, Anita Suresh, Timothy C. Rodwell, Rebecca E. Colman

“…Complete assay failure rates were low for LPAs (4.9%) and ONT (5.0%) and moderately higher for GenoScreen (8.6%), with differences in single-target failures across all assays. …”
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Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches by Wenjie Han, Wenjie Han, Yuhang Zhou, Yuhang Zhou, Yiwen Wang, Yiwen Wang, Xiaolin Liu, Tao Sun, Tao Sun, Junnan Xu, Junnan Xu, Junnan Xu

“…Among eight machine learning algorithms evaluated, the optimal model was selected to construct a predictive framework for immunotherapy response.ResultsMicrobial α-diversity was significantly elevated in responders compared to non-responders, with antibiotic administration further amplifying this difference—most notably at the species level. …”
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What has changed in the attitude of health workers towards vaccination after the pandemic COVID-19 by S. M. Kharit, L. V. Romanov, Yu. E. Konstantinova, S. A. Bogdan

“…There is a significant difference between confirming the answer about the need for vaccination and vaccinating yourself, as well as evaluating the effectiveness of the vaccine (even for measles vaccines, 90.7% say they need to be vaccinated, only 83.5% are vaccinated and only 76.7% are confident in the effectiveness of the vaccine. …”
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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…Using machine-learning algorithms, specifically Random Forest, has yielded significant insights into the factors influencing Ethiopia’s unimproved water supply. …”
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