Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Furthermore, a novel Attention-augmented Spatial-Temporal Graph Convolutional Network (AST-GCN) is developed for reliably identifying the action in each frame, enabling accurate computation of key kinematic features for fall risk prediction. Experimental evaluations on a dataset of 450 FSTS test videos demonstrate the high performance of <sc>FRAVM</sc>, with detection accuracy, F1 score, and ROC-AUC achieving 88.64%, 88.58%, and 98.86%, respectively. …”
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Automatic identification of hard and soft tissue landmarks in cone-beam computed tomography via deep learning with diversity datasets: a methodological study by Yan Jiang, Canyang Jiang, Bin Shi, You Wu, Shuli Xing, Hao Liang, Jianping Huang, Xiaohong Huang, Li Huang, Lisong Lin

“…To evaluate the accuracy of our algorithm, we determined the mean absolute error along the x-, y-, and z-axes and calculated the mean radial error (MRE) between the reference landmark and predicted landmark, as well as the successful detection rate (SDR). …”
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Biomarker and clinical data–based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal st... by Eva María Arriero-País, María Auxiliadora Bajo-Rubio, Roberto Arrojo-García, Pilar Sandoval, Guadalupe Tirma González-Mateo, Patricia Albar-Vizcaíno, Gloria del Peso-Gilsanz, Marta Ossorio-González, Pedro Majano, Manuel López-Cabrera, Gloria del Peso-Gilsanz

“…Linear discriminant analysis (LDA) discerns among transfer to haemodialysis or death, predicts whether the cause of PD end is ultrafiltration failure (UFF) or cardiovascular disease (CVD) and anticipates the type of CVD (receiver operating characteristic curve under the area&gt;0.71).Discussion Our combination of longitudinal PD datasets, attribute shrinkage and gold-standard algorithms with overfitting testing and class imbalance ensures robust predictions in PD. …”
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Snow Depth Retrieval Using Detrended SNR From GNSS-R With Bidirectional GRU by Wei Liu, Zihui Lin, Yuan Hu, Aodong Tian, Xintai Yuan, Jens Wickert

“…Snow depth monitoring is crucial for hydrology, climate research, and avalanche prediction. While traditional global navigation satellite system (GNSS) reflectometer methods offer cost-effective snow thickness retrieval, they suffer from poor accuracy and robustness, especially in complex terrains and extreme weather. …”
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Vision-Guided Maritime UAV Rescue System with Optimized GPS Path Planning and Dual-Target Tracking by Suli Wang, Yang Zhao, Chang Zhou, Xiaodong Ma, Zijun Jiao, Zesheng Zhou, Xiaolu Liu, Tianhai Peng, Changxing Shao

“…Furthermore, a dual-target-tracking algorithm—integrating motion prediction with color-based landing zone recognition—achieves a 96% success rate in precision landings under dynamic conditions. …”
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Plasma cfDNA multi-omic biomarkers profiling for detection and stratification of gastric carcinoma by Shiyi Song, Xiuli Zhang, Pin Cui, Weihuang He, Jiyuan Zhou, Shubing Wang, Yong Xiong, Shu Xu, Xiaohui Lin, Guozeng Huang, Xiaohua Tan, Qinglong Xu, Yongling Liu, Qingqun Li, Kehua Yuan, Mingji Feng, Hanming Lai, Hui Yang, Shaorong Zhang

“…And these biomarkers were extracted from WGS data to build machine learning algorithm based classifiers, prediction models, to discriminate GC patients from healthy individuals, achieving extremely high precision of sensitivity at 94.87% and specificity at 99.35%. …”
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Rapid discrimination and quantification of chemotypes in Perillae folium using FT-NIR spectroscopy and GC–MS combined with chemometrics by Dai-xin Yu, Cheng Qu, Jia-yi Xu, Jia-yu Lu, Di-di Wu, Qi-nan Wu

“…Furthermore, the main components of perilla ketone and isoegomaketone in PF were successfully quantified using partial least squares regression models, with prediction to deviation values of 3.76 and 2.59, respectively. …”
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Radiomic Features of Mesorectal Fat as Indicators of Response in Rectal Cancer Patients Undergoing Neoadjuvant Therapy by Francesca Treballi, Ginevra Danti, Sofia Boccioli, Sebastiano Paolucci, Simone Busoni, Linda Calistri, Vittorio Miele

“…The aim was to assess the potential presence of predictive factors for favorable or unfavorable responses to neoadjuvant chemoradiotherapy, thereby optimizing treatment management and improving personalized clinical decision-making. …”
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Association between international normalized ratio-to-albumin ratio and mortality in critically ill patients with gastrointestinal bleeding: a retrospective MIMIC-IV database study by Xingyi Yang, Shasha Ying, Lihong Lv, Yishu Ji, Jiaqian Ying, Huyan Ke

“…Abstract Background While the international normalized ratio-to-albumin ratio (PTAR) is an established independent prognostic indicator for various diseases, its predictive value for clinical outcomes in critically ill patients with acute gastrointestinal bleeding (GIB) has not been systematically evaluated. …”
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Expected Impact of Rubin Observatory LSST on NEO Follow-up by Tom Wagg, Mario Juric, Peter Yoachim, Jake Kurlander, Sam Cornwall, Joachim Moeyens, Siegfried Eggl, R. Lynne Jones, Peter Birtwhistle

“…We consider follow-up prioritisation strategies to lessen the impact on the NEO follow-up system. We develop an algorithm that predicts (with 68% accuracy) whether Rubin itself will self recover any given tracklet; external follow-up of such candidates can be deprioritized. …”
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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

“…The machine learning models predicted performance 400 times faster than traditional performance simulations. …”
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Evaluation of AI-Powered Routine Screening of Clinically Acquired cMRIs for Incidental Intracranial Aneurysms by Christina Carina Schmidt, Robert Stahl, Franziska Mueller, Thomas David Fischer, Robert Forbrig, Christian Brem, Hakan Isik, Klaus Seelos, Niklas Thon, Sophia Stoecklein, Thomas Liebig, Johannes Rueckel

“…<b>Results</b>: The algorithm demonstrates high sensitivities (100% for findings >4 mm in diameter), a 17.8% MRA alert rate and positive predictive values of 11.5–43.8% (depending on whether inconclusive findings are considered or not). …”
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Automatic Detection of Occluded Main Coronary Arteries of NSTEMI Patients with MI-MS ConvMixer + WSSE Without CAG by Mehmet Cagri Goktekin, Evrim Gul, Tolga Çakmak, Fatih Demir, Mehmet Ali Kobat, Yaman Akbulut, Ömer Işık, Zehra Kadiroğlu, Kürşat Demir, Abdulkadir Şengür

“…Moreover, to maximise the classifier performance, the WSSE algorithm was developed to adjust the classification prediction value according to the feature importance weights. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…This framework utilizes quantum-inspired least square support vector machine (LS-SVM) classifier. This algorithm is used to enhance the classification accuracy in terms of reducing false predictions while minimizing the training time. …”
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Performance of the Oncuria-Detect bladder cancer test for evaluating patients presenting with haematuria: results from a real-world clinical setting by Ian Pagano, Zhen Zhang, Michael Luu, Sergei Tikhonenkov, Florence Le Calvez-Kelm, Steve Goodison, Toru Sakatani, Kaoru Murakami, Takashi Kobayashi, Patrice Avogbe, Howard Kim, Riko Lee, Arnaud Manel, Emmanuel Vian, Charles J. Rosser, Hideki Furuya

“…In the test set, the Oncuria-Detect assay correctly identified bladder cancer in 62 of 73 cases resulting in a sensitivity of 85%, a specificity of 72%, and a negative predictive value (NPV) of 95%. The performance of Oncuria was similar for both low-grade/low-stage and high-grade/high-stage. …”
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Modeling the impact of climate change on suitable areas for the underutilized crop Cyperus esculentus (tiger nut) and implications for production expansion and conservation in Togo... by Koffi Kibalou Palanga, Anissou Bawa, Jacques Idohou Kadjogbé Ayena, Dowo Michée Adjacou, Thierry Dèhouégnon Houehanou, Gérard Nounagnon Gouwakinnou, Armand Kuyema Natta

“…Currently, 40% of the country is suitable for tiger nut cultivation, with optimal habitats concentrated in the south. Future scenarios predict a strong decrease of suitable areas in the north and a slight expansion towards the center and south. …”
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FPGA Implementation for 24.576-Gbit/s Optical PAM4 Signal Transmission with MLP-Based Digital Pre-Distortion by Sheng Hu, Tianqi Zheng, Chengzhen Bian, Xiongwei Yang, Xinda Sun, Zonghui Zhu, Yumeng Gou, Yuanxiao Meng, Jie Zhang, Jingtao Ge, Yichen Li, Kaihui Wang

“…A multilayer perceptron (MLP) can overcome this limitation by predicting errors and generating pre-distorted signals, thus replacing the extensive storage requirements of LUTs with minimal computational resources. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…Performances are investigated by means of the test set’s prediction metrics for several instances of the model’s input. …”
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Estimating genomic relationships of metafounders across and within breeds using maximum likelihood, pseudo-expectation–maximization maximum likelihood and increase of relationships... by Andres Legarra, Matias Bermann, Quanshun Mei, Ole F. Christensen

“…Considering metafounders might be advantageous in pedigree best linear unbiased prediction (BLUP) or single-step genomic BLUP. Existing methods to estimate relationships across metafounders $${\varvec{\Gamma}}$$ Γ are not well adapted to highly unbalanced data, genotyped individuals far from base populations, or many unknown parent groups (within breed per year of birth). …”
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Conjecture Interaction Optimization Model for Intelligent Transportation Systems in Smart Cities Using Reciprocated Multi-Instance Learning for Road Traffic Management by Abdullah Faiz Al Asmari, Ahmed Almutairi, Fayez Alanazi, Tariq Alqubaysi, Ammar Armghan

“…The MIL algorithm integrates multi-instance learning into the interaction labelling process, enhancing the routing prediction by differentiating between reliable and erroneous data. …”
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