Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
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Assessing the Cause of Death for Men with Prostate Cancer Using Official Mortality Statistics or a Dedicated Cause of Death Committee: Results from 30-year ERSPC Rotterdam Data by Sebastiaan Remmers, Ivo I. de Vos, Frederique B. Denijs, Renée C.A. Leenen, Tycho M.T.W. Lock, Arjen Noordzij, Wim J. Kirkels, Chris H. Bangma, Monique J. Roobol

“…Extrapolation of our findings to 30 yr of follow-up would result in an expected risk reduction of PCSM of 30% using data from the CODC and 33% using official statistics in favor of screening. …”
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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

“…The new GPU-optimised NNPDF code results in a speed-up of up to two orders of magnitude, a stabilisation of the memory requirements, and a reduction in energy consumption of up to 90% as compared to sequential CPU-based model training. …”
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FAQIVS: Face Query-based Interactive Video Synopsis* by Nagavani Chandrasekaran, Yogameena Balasubramanian

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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…To increase productivity, precision, and reproducibility, researchers are increasingly integrating artificial intelligence (AI)-based techniques into IVOCT analysis pipelines. Machine learning algorithms, trained on labelled datasets, have demonstrated robust classification of various plaque types. …”
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RETRACTED: CHOICE OF OSTEOFIXATION OF EPITHESIS IN TOTAL DEFECT OF THE MAXILLOFACIAL REGION by N. I. Tcherezova

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METODE KLASIFIKASI JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA MAHASISWA STATISTIKA UNIVERSITAS TERBUKA by Siti Hadijah Hasanah, Sri Maulidia Permatasari

“…Backpropagation Artificial Neural Network (ANN) is an ANN that uses a supervised learning algorithm. The purpose of this study is to determine the parameters and measure the accuracy of the classification accuracy of the student status of the Open University Statistics Study Program. …”
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Research on knowledge concept extraction method based on few-shot learning and chain-of-thought prompting by SHE Linlin, XIONG Longyang, LU Xuesong

“…Knowledge concept extraction has important application value in the fields of education, medical care, and finance. Knowledge concept extraction is a sub-task of named entity recognition. …”
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A deep learning approach for accurate COVID-19 diagnosis from x-ray images using OBLMPA by Xiaohua Li, Shuai Fu

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Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning by Yanzi Li, Cai Chen, Fuqiang Liu, Jian Wang

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Using Stacks for Image Segmentation Based on Region Growing by V. Yu. Tsviatkou

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Research on knowledge concept extraction method based on few-shot learning and chain-of-thought prompting by SHE Linlin, XIONG Longyang, LU Xuesong

“…Knowledge concept extraction has important application value in the fields of education, medical care, and finance. Knowledge concept extraction is a sub-task of named entity recognition. …”
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Tutors' perceptions of ICTs in promoting computational thinking among pre-service teachers in Tanzanian colleges by Vicky Mrosso, Placidius Ndibalema, Abdon Ephrem

“…The findings revealed that tutors dominantly perceive CT as a digital literacy skill while ignoring the cognitive processes that underlie CT skills such as abstraction, algorithmic thinking, decomposition, and pattern recognition. …”
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Several aspects of conservative treatment of patients with cervical osteochondrosis by O. V. Sklyarenko, Z. V. Koshkaryova, V. A. Sorokovikov

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Joint Relay Ordering and Linear Finite Field Network Coding for Multiple-Source Multiple-Relay Wireless Sensor Networks by Yulun Cheng, Longxiang Yang

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Assessing safety in horizontal curves using surrogate safety measures and machine learning by Navid Nadimi, Hojjat Fathipour, Abbas Sheykhfard

“…In this paper, with the help of a decision tree algorithm and SSMs; the impact of different variables is assessed on the safety of HCs. …”
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Combinatorial-Semantic Analysis of Collocations as a Method of Linguistic Research (on the Example of Colour Collocations Formed by an Adjective Type) by M. V. Vlavatskaya

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Approaches to Assessing Knowledge Level of Business-Organization by S. N Kukushkin, O. E. Kalenov

“…In conclusion algorithm of estimating the index of knowledge level is described and advantages of this method are demonstrated.…”
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Accurate detection of critical LLFs and LGFs in PV arrays based on deep reinforcement learning using proximal policy optimization (PPO) by Sherko Salehpour, Aref Eskandari, Amir Nedaei, Mohammad Gholami, Mohammadreza Aghaei

“…To address these challenges, the present paper proposes a deep reinforcement learning (DRL)-based model to detect, classify, and assess the severity of all and specifically critical LLFs and LGFs in PV arrays using the proximal policy optimization (PPO) algorithm. Additionally, to carry out the dataset dimensionality reduction, thus simplifying the training process, a two-stage feature engineering process has been implemented, including a feature importance finding stage using the permutation technique and a feature selection stage. …”
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Multi-omic signatures of host response associated with presence, type, and outcome of enterococcal bacteremia by Charlie Bayne, Dominic McGrosso, Concepcion Sanchez, Leigh-Ana Rossitto, Maxwell Patterson, Carlos Gonzalez, Courtney Baus, Cecilia Volk, Haoqi Nina Zhao, Pieter Dorrestein, Victor Nizet, George Sakoulas, David J. Gonzalez, Warren Rose

“…Altogether, this study aims to culminate in the creation of objective risk stratification algorithms—a pivotal step toward enhancing patient management and care. …”
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