Enhancing Sentiment-Driven Recommender Systems With LLM-Based Feature Engineering: A Case Study in Drug Review Analysis by Samuel Matia Kangoni, Obed Tshimanga Tshipata, Pierre Sedi Nzakuna, Vincenzo Paciello, Jean-Gilbert Mbula Mboma, Jean-Robert Makulo, Kyandoghere Kyamakya

“…These embeddings are used in sequential models (Bi-LSTM, CNN) and non-sequential models (Random Forest, DNN, ExtraTreesClassifier). The Random Forest model with LLM2Vec achieves the best performance, with 0.93 accuracy, F1-scores of 0.95 (positive) and 0.88 (negative), and precision scores of 0.93 (positive) and 0.94 (negative). …”
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Additional findings in prostate MRI by Fabio Porões, Paraskevi Karampa, Thomas Sartoretti, Hugo Najberg, Johannes M. Froehlich, Carolin Reischauer, Harriet C. Thoeny

“…One hundred and twenty-three (2.4% of all findings) extra-prostatic PCa related AFs were found in 106 (8.3% of all patients) patients. …”
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Characterization of protein glycosylation in an Asgard archaeon by Satoshi Nakagawa, Hiroyuki Imachi, Shigeru Shimamura, Saeko Yanaka, Hirokazu Yagi, Maho Yagi-Utsumi, Hiroyuki Sakai, Shingo Kato, Moriya Ohkuma, Koichi Kato, Ken Takai

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Crop Classification and Yield Prediction Using Robust Machine Learning Models for Agricultural Sustainability by Abid Badshah, Basem Yousef Alkazemi, Fakhrud Din, Kamal Z. Zamli, Muhammad Haris

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Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

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A comparison of tools used for tuberculosis diagnosis in resource-limited settings: a case study at Mubende referral hospital, Uganda. by Adrian Muwonge, Sydney Malama, Barend M de C Bronsvoort, Demelash Biffa, Willy Ssengooba, Eystein Skjerve

“…The three-predictor screening algorithm with and without DZM classified 50% and 33% of the true cases respectively, while the adjusted algorithm with DZM classified 78% of the true cases.…”
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Prediction of prostate biopsy outcomes at different cut-offs of prostate-specific antigen using machine learning: a multicenter study by Mostafa A. Arafa, Karim H. Farhat, Sherin F. Aly, Farrukh K. Khan, Alaa Mokhtar, Abdulaziz M. Althunayan, Waleed Al-Taweel, Sultan S. Al-Khateeb, Sami Azhari, Danny M. Rabah

“…Results The metrics for Random Forest, Extra Tree, and Decision Tree algorithms showed excellent capability in classifying the outcomes of prostate biopsy for the two PSA cut-offs. …”
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An interpretable machine learning model for predicting bone marrow invasion in patients with lymphoma via 18F-FDG PET/CT: a multicenter study by Xinyu Zhu, Denglu Lu, Yang Wu, Yanqi Lu, Liang He, Yanyun Deng, Xingyu Mu, Wei Fu

“…Among the tested models, the ExtraTrees classifier achieved the best performance. …”
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Runoff Generation Mechanisms of Flash Flood Forecasting in Guanshan River Basin by LI Miao, TANG Wen-jian, DONG Lin-yao, ZENG Yu-jie

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A new clinical classification of congenital biliary dilatation – HUAXI CBD classification by Zhenyu Xie, Siyu Pu, Shuguang Jin, Bo Xiang, Jiayin Yang, Lvnan Yan

“…Methods Based on the preoperative imaging data of patients with CBD admitted to the Department of Pediatric Surgery of West China Hospital of Sichuan University, from January 2015 to December 2018, a new classification of CBD was accomplished according to the site of bile duct dilatation lesions, which was named HUAXI CBD classification. The CBD was classified into 4 types: type I (distal extra-hepatic bile duct dilatation), type II (distal extra-hepatic combined with right and left primary hepatic bile duct dilatation), type III (extra-hepatic combined with secondary and above hepatic bile duct dilatation), and type IV (intra-hepatic bile duct dilatation). …”
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Predicting agricultural drought in central Europe by using machine learning algorithms by Endre Harsányi

“…Overall, 16 years were identified as droughts by SPEI-3 to SPEI-12 in the 1st three decades (1926–1956), 12 drought years from 1957 to 1986 and 21 drought years from 1987 to 2020. …”
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Millisecond‐scale behaviours of plankton quantified in vitro and in situ using the Event‐based Vision Sensor by Susumu Takatsuka, Norio Miyamoto, Hidehito Sato, Yoshiaki Morino, Yoshihisa Kurita, Akinori Yabuki, Chong Chen, Shinsuke Kawagucci

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Paleovegetation Community and Paleoclimate Succession in Middle Jurassic Coal Seams in Eastern Coalfields in Dzungaria Basin, China by Xingli Wang, Shuo Feng, Wenfeng Wang, Qin Zhang, Jijun Tian, Changcheng Han, Meng Wang

“…Therefore, the aim of this study was to classify the paleovegetation types and develop paleoclimate succession models of the extra-thick coal seams. …”
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Effect of Extraction Method on Organoleptic, Physicochemical Properties and Some Biological Activities of Olive Oil from the Algerian Chemlal Variety by Sara Messad, Souhila Bensmail, Omar Salhi, Djamila Djouahra Fahem

“…Antimicrobial activity analysis was performed using the agar diffusion technique against five strains.Results: The analyses revealed that olive oil obtained by manual extraction is classified in the extra virgin category, according to the International Olive Oil Council. …”
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Establishment of an MRI-based radiomics model for distinguishing between intramedullary spinal cord tumor and tumefactive demyelinating lesion by Zifeng Zhang, Ning Li, Yuhang Qian, Huilin Cheng

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An Ensemble Fuzzy-Based Deep Learning Framework for Automatic Detection of Children with ADHD From EEG Signal by Jalil Manafian, Mehdi Fazli, Onur Ilhan, Subhiya Zeynalli, Sukaina Tuama Ghafel

“…These constructed images are then fed into an ensemble deep framework. Three transfer learning models, namely VGGNet, Inception V3, and Inception ResNet V2, are utilized in this task, enhanced with extra layers to catch data-specific attributes. …”
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EnsembleNPPred: A Robust Approach to Neuropeptide Prediction and Recognition Using Ensemble Machine Learning and Deep Learning Methods by Supatcha Lertampaiporn, Warin Wattanapornprom, Chinae Thammarongtham, Apiradee Hongsthong

“…EnsembleNPPred employs a majority voting mechanism to aggregate the outputs from three classifiers: Support Vector Machine (SVM), Extra Trees (ET), and a CNN-based DL model. …”
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About the neurolinguistics of the implicatures: abstract of a study by Juliano Luís Fontanari

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Incidence and risk factors for post-penetrating keratoplasty glaucoma: A systematic review and meta-analysis. by Suqian Wu, Jianjiang Xu

“…Exact PKKG definitions used in the literature could be classified in to three subgroups: I, ocular hypertension (> 21mmHg) after PK; II, I plus > 4 weeks medical treatment required; III, II plus treatment escalation among patients with preexisting glaucoma. …”
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Endovascular treatment for intracranial infectious aneurysms Tratamento endovascular de aneurismas infecciosos intracranianos by Eduardo Wajnberg, Fernanda Rueda, Edson Marchiori, Emerson L. Gasparetto

“…RESULTS: Endovascular treatment was executed technically uneventfully in all patients. Three patients had favorable clinical outcome: two were classified as Glasgow Outcome Scale 4/5, and one had total neurological recovery (GOS 5/5). …”
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