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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A Memristive Hyperjerk Chaotic System: Amplitude Control, FPGA Design, and Prediction with Artificial Neural Network by Ran Wang, Chunbiao Li, Serdar Çiçek, Karthikeyan Rajagopal, Xin Zhang

“…Finally, the proposed memristive hyperjerk system is successfully predicted with artificial neural networks for AI based engineering applications.…”
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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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Prediction of the transient coolant jet released from the nose cone at supersonic flow via machine learning by A. B. Ali, M. Yasiri, Pooya Ghodratallah, Kamal Sharma, Nimesh Raj, S. Abdul Ameer, Mohammed Yaseen Abdullah, Abbas Hameed Abdul Hussein, Mohammed Y. Al-Khuzaie, M. Ahmedi

“…The POD modes for the efficient prediction of the different flow variables are defined. …”
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PHYSICS-DRIVEN FEATURE CREATION TO IMPROVE MACHINE LEARNING MODELS PERFORMANCE FOR OIL PRODUCTION RATE PREDICTION by Eghbal Motaei, Seyed Mehdi Tabatabai, Tarek Ganat, Ahmad Khanifar, Sulaiman Dzaiy, Timur Chis

Subjects: “…oil rate prediction…”
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A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification by Ismaili Burim, Besimi Adrian

“…This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics.…”
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A two-step machine learning approach for predictive maintenance and anomaly detection in environmental sensor systems by Saiprasad Potharaju, Ravi Kumar Tirandasu, Swapnali N. Tambe, Devyani Bhamare Jadhav, Dudla Anil Kumar, Shanmuk Srinivas Amiripalli

“…Such an approach addresses a critical gap, transforming raw, unlabeled IoT sensor data into actionable insights for predictive maintenance. This methodology provides a scalable and robust real-time anomaly detection and sensor fault prediction methodology that greatly enhances the reliability of the environmental monitoring systems and advances the intelligent infrastructure management. • Combines Isolation Forest for anomaly labeling and supervised models for anomaly prediction. • Scalable and adaptable for diverse IoT applications for environmental monitoring. • Provides actionable insights through anomaly visualization, revealing patterns in sensor performance.…”
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High-Speed Data-Driven Methodology for Real-Time Traffic Flow Predictions: Practical Applications of ITS by Hyun-ho Chang, Byoung-jo Yoon

“…To overcome this critical issue successfully, a high-speed KNN-NPR framework, capable of generating short-term traffic volume predictions, is proposed in this study. The proposed method is based on a two-step search algorithm, which has the two roles of building promising candidates for input data during nonprediction times and identifying decision-making input data for instantaneous predictions at the prediction point. …”
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Exploring the feasibility of near-infrared spectroscopy in analyzing and predicting the chemical and biochemical changes of chitin-amended soils by Ken Abamba Omwange, Ana Chen, Renfu Lu, Carly Daiek, Julie Celini, Yan Liu

“…The second derivative model for 900-1,660 nm yielded high predictive accuracy with R² values of 0.915, 0.892, and 0.810 for pH, total DNA, and trpB gene DNA respectively. …”
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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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Predictive Values of Preoperative Tests for Difficult Laryngoscopy and Intubation in Adult Patients at Tikur Anbessa Specialized Hospital by Tadese Tamire, Habtamu Demelash, Wosenyeleh Admasu

“…Nevertheless, the need to predict potentially difficult tracheal intubation has received a little attention. …”
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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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The role of host plants, land cover and bioclimate in predicting the invasiveness of Aromia bungii on a global scale by Enrico Ruzzier, Seunghyun Lee, Pietro Tirozzi, Valerio Orioli, Andrea Di Giulio, Olivia Dondina, Luciano Bani

“…To improve the predictive power of the modelling framework, a habitat suitability model (HSM), which includes host plants, was combined with a bioclimatic suitability model (BSM), both of which were calibrated on native occurrences. …”
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Model Optimization Analysis of Customer Churn Prediction Using Machine Learning Algorithms with Focus on Feature Reductions by Seyed Mohammad Sina Mirabdolbaghi, Babak Amiri

“…In this paper, a model for predicting light GBM churn is proposed. The model consists of five steps. …”
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Computational predictions of magnetic resonance acoustic radiation force imaging for breast cancer focused ultrasound therapy by Chloe K. Nelson, Michelle Kline, Allison Payne, Christopher R. Dillon

“…The displacement magnitudes of the simulations underestimated the MR-ARFI measurements by 82% (SD: 5.6%).Conclusions The agreement between MR-ARFI measurements and simulations demonstrates that HAS can predict the in vivo focal location in heterogeneous tissues, though accurate patient-specific properties are needed to improve predictions of tissue displacement magnitude. …”
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Speeding Violation Type Prediction Based on Decision Tree Method: A Case Study in Wujiang, China by Zeyang Cheng, Jian Lu, Zhenshan Zu, Yunxuan Li

“…Before the prediction, a speeding violation influence factor analysis based on the binary logical regression model is proposed. …”
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Prediction model of PTO shaft fatigue damage considering sandy loam and loam in rotary-tillage operation by Moon-Kyeong Jang, Seung-Jun Kim, Young-Hoo Cho, Ju-Seok Nam

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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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