Impact of climate change on the distribution of Isaria cicadaeMiquel in China: predictions based on the MaxEnt model by Zhipeng He, Habib Ali, Junhao Wu, Zhiqian Liu, Xinju Wei, Zhihang Zhuo

“…Understanding its potential distribution is essential for promoting sustainable harvesting practices.MethodsThis study utilizes the MaxEnt model, combined with known distribution records and 22 environmental variables, to predict the potential distribution of I. cicadae under three representative emission scenarios (CMIP6: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the 2050s and 2070s.ResultsThe analysis identifies seven key environmental variables influencing the habitat suitability of I. cicadae: the mean temperature of the driest quarter (bio09), the mean temperature of the wettest quarter (bio08), precipitation in the wettest month (bio16), the mean diurnal range (bio02), isothermality (bio03), elevation, and slope. …”
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Association of HLA-B27 Gene and Rheumatoid Arthritis: Analysis of Potential Role as a Predictive Biomarker by Karzan Ghafur Khidhir, Baban Ahmad, Dana Khdr Sabir

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Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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New Parameters for Impedance–pH Monitoring in Diagnosing Gastroesophageal Reflux Disease and Predicting its Severity by O. A. Storonova, A. S. Trukhmanov, A. A. Makushina, A. V. Paraskevova, V. T. Ivashkin

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Ultrasound evaluation of gallbladder wall thickness for predicting severe dengue: a systematic review and meta-analysis by Amirhossein Shahsavand Davoudi, Hamid Harandi, Reza Samiee, Shayan Forghani, Keyhan Mohammadi, Maryam Shafaati

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Caregiver burden and its prevalence, measurement scales, predictive factors and impact: a review with an Asian perspective by Yu Xian Loo, Shi Yan, Lian Leng Low

“…The primary aim of this review is to summarise the prevalence of caregiver burden and its measurement scales, predictive factors and impact in Singapore. PubMed® and Scopus® databases were searched using the key terms ‘caregiver’, ‘burden’, ‘stress’, ‘strain’ and ‘Singapore’. …”
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A volume-preserving model for predicting the geometry of traces produced by drop-on-demand 3D printing by R. Zamora, F. Faura, J. López, J. Hernández

“…A model is proposed to predict the geometry of traces generated by molten metal droplet deposition on a flat solid surface. …”
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A Hybrid Machine Learning Framework for Soccer Match Outcome Prediction: Incorporating Bivariate Poisson Distribution by Chen Zhong An

“…While Random Forests achieved the highest accuracy (56.25%), predicting draws remains challenging. The study highlights the potential for improved prediction systems and suggests future research in advanced draw prediction techniques and profitability analysis, the paper provides research directions for researchers in related fields.…”
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Prediction of High-ozone Events Using GAM, SMOTE, and Tail Dependence Approaches in Texas (2005–2019) by Benjamin Brown-Steiner, Xiong Zhou, Matthew J. Alvarado, Brook T. Russell

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Carcinoembryonic antigen trajectory predicts pathological complete response in advanced gastric cancer after neoadjuvant chemotherapy by Yonghe Chen, Yonghe Chen, Yonghe Chen, Dan Liu, Kaikai Wei, Yi Lin, Yi Lin, Yi Lin, Zhong Wang, Qian Sun, Huashe Wang, Huashe Wang, Huashe Wang, Junsheng Peng, Junsheng Peng, Junsheng Peng, Lei Lian, Lei Lian, Lei Lian

“…AimsThis study aims to develop a simple, clinically applicable classification system to predict pCR based on carcinoembryonic antigen (CEA) trajectory during NAC.MethodsThis study included 366 AGC patients who received NAC followed by radical gastrectomy. …”
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Predicting ixodid tick distribution in Tamil Nadu domestic mammals using ensemble species distribution models by Ayyanar Elango, Hari Kishan Raju, Ananganallur Nagarajan Shriram, Ashwani Kumar, Manju Rahi

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Personalized prediction of glycemic responses to food in women with diet-treated gestational diabetes: the role of the gut microbiota by Polina V. Popova, Artem O. Isakov, Anastasiia N. Rusanova, Stanislav I. Sitkin, Anna D. Anopova, Elena A. Vasukova, Alexandra S. Tkachuk, Irina S. Nemikina, Elizaveta A. Stepanova, Angelina I. Eriskovskaya, Ekaterina A. Stepanova, Evgenii A. Pustozerov, Maria A. Kokina, Elena Y. Vasilieva, Lyudmila B. Vasilyeva, Soha Zgairy, Elad Rubin, Carmel Even, Sondra Turjeman, Tatiana M. Pervunina, Elena N. Grineva, Omry Koren, Evgeny V. Shlyakhto

“…Abstract We developed a prediction model for postprandial glycemic response (PPGR) in pregnant women, including those with diet-treated gestational diabetes mellitus (GDM) and healthy women, and explored the role of gut microbiota in improving prediction accuracy. …”
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Examine the Role of Psychological Resilience in Predicting Social and Professional Performance in Patients with Diabetes, Multiple Sclerosis, and Rheumatism by Ahmad S Alsheikh Al, Ashraf Alqudah

“…Results revealed that psychological resilience positively predicted social and occupational functions among all illnesses. …”
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Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania by Ngong'Ho Bujiku Sende, Snehanshu Saha, Leon Ruganzu, Saibal Kar

“…Our policy recommendations draw on the results of the algorithmic predictions.…”
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Immune cell profiles and predictive modeling in osteoporotic vertebral fractures using XGBoost machine learning algorithms by Yi-Chou Chen, Hui-Chen Su, Shih-Ming Huang, Ching-Hsiao Yu, Jen-Huei Chang, Yi-Lin Chiu

“…Methods This study aims to investigate the xCell signature-based immune cell profiles in osteoporotic patients with and without vertebral fractures, utilizing advanced predictive modeling through the XGBoost algorithm. Results Our findings reveal an increased presence of CD4 + naïve T cells and central memory T cells in VF patients, indicating distinct adaptive immune responses. …”
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ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction. by Yunyun Dong, Yuanrong Zhang, Yuhua Qian, Yiming Zhao, Ziting Yang, Xiufang Feng

“…Experimental evaluations further illuminate ASGCL's proficiency in predicting drug responses, offering a potent tool for guiding clinical decision-making in cancer therapy.…”
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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review by Md Mohshin Ali, Md. Arif Hossen, Azrina Abd Aziz

“…Emerging Machine learning (ML) techniques have significantly improved the predictive performance and operational efficiency of photocatalytic systems. …”
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AI-Driven Meat Food Drying Time Prediction for Resource Optimization and Production Planning in Smart Manufacturing by Rajnish Rakholia, Andres L. Suarez-Cetrulo, Manokamna Singh, Ricardo Simon Carbajo

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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer by Yuan Zeng, Yuhao Chen, Dandan Zhu, Jun Xu, Xiangting Zhang, Huiya Ying, Xian Song, Ruoru Zhou, Yixiao Wang, Fujun Yu

“…Therefore, it is particularly important to find a suitable way to predict the risk of postoperative occurrence of DVT in GC patients. …”
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A Hybrid Particle Swarm Optimization-Tuning Algorithm for the Prediction of Nanoparticle Morphology from Microscopic Images by Abhishek Singh, Thaseem Thajudeen

“…Results show that the hybrid algorithm can closely predict the 3-dimensional structures from the projection images with less than 10% difference in the predicted 3-dimensional properties including mobility diameter and radius of gyration.…”
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