A Spatial-Temporal Self-Attention Network (STSAN) for Location Prediction by Shuang Wang, AnLiang Li, Shuai Xie, WenZhu Li, BoWei Wang, Shuai Yao, Muhammad Asif

“…Our method STSAN gains about 39.8% Acc@1 and 4.4% APR improvements against the strongest baseline on New York City dataset.…”
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Incremental Graph Regulated Nonnegative Matrix Factorization for Face Recognition by Zhe-Zhou Yu, Yu-Hao Liu, Bin Li, Shu-Chao Pang, Cheng-Cheng Jia

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ECG-based transfer learning for cardiovascular disease: A scoping review by Sharifah Noor Masidayu Sayed Ismail, Siti Fatimah Abdul Razak, Nor Azlina Ab Aziz

“…Our analysis of over 70 studies published in the last six years indicates that arrhythmias are the most extensively studied CVD, with the MIT-BIH arrhythmia dataset being the most commonly used in previous research. …”
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Use of testosterone replacement therapy in the rehabilitation of patients with intensive care unit-associated weakness and hospital-associated deconditioning: the Singapore General... by Geoffrey Sithamparapillai Samuel, Du Soon Swee

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Towards Transparent Diabetes Prediction: Combining AutoML and Explainable AI for Improved Clinical Insights by Raza Hasan, Vishal Dattana, Salman Mahmood, Saqib Hussain

“…Using the Pima Indian Diabetes dataset, we developed an ensemble model with 85.01% accuracy leveraging AutoGluon’s AutoML framework. …”
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Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis by Paul Wighton, Tim K. Lee, Greg Mori, Harvey Lui, David I. McLean, M. Stella Atkins

“…We evaluate both models' ability to segment a challenging dataset consisting of 116 images and compare our results to 5 previously published methods.…”
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LDDP-Net: A Lightweight Neural Network with Dual Decoding Paths for Defect Segmentation of LED Chips by Jie Zhang, Ning Chen, Mengyuan Li, Yifan Zhang, Xinyu Suo, Rong Li, Jian Liu

“…Experimental results demonstrate that LDDP-Net achieves an mIoU (mean Intersection over Union) of 90.29% on the chip dataset, with parameter numbers and FLOPs (Floating Point Operations) of 2.98 M and 2.24 G, respectively. …”
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Detection of cervical cell based on multi-scale spatial information by Gang Li, Xinyu Fan, Chuanyun Xu, Pengfei Lv, Ru Wang, Zihan Ruan, Zheng Zhou, Yang Zhang

“…Experiments on the CDetector dataset achieved an Average Precision (AP) of 65.3%, outperforming the state-of-the-art (SOTA) methods.…”
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Goal and shot prediction in ball possessions in FIFA Women’s World Cup 2023: a machine learning approach by Iyán Iván-Baragaño, Antonio Ardá, José L. Losada, Rubén Maneiro

“…The predictive capacity was tested using Random Forest and XGBoost and finally and SHAP values were calculated and visualized to understand the influence of the predictors.ResultsRandom Forest technique showed greater efficacy, with recall and sensitivity above 93% in the resampled dataset. However, recall on the original test sample was 13% (Success = Shot or Goal) and 0% (Success = Goal), demonstrating the models’ inability to predict rare events in football, such as goals. …”
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Low-Rank Adaptation of Pre-Trained Large Vision Models for Improved Lung Nodule Malignancy Classification by Benjamin P. Veasey, Amir A. Amini

“…The annotations for the NLSTx dataset are also released with this paper on GitHub at <uri>https://github.com/benVZ/NLSTx</uri>.…”
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Variable power functional dilution adjustment of spot urine by Thomas Clemens Carmine

“…The generalizability of V-PFCRC was evaluated using large spot-urinary datasets for four additional metals and an extensive dataset of urinary iodine levels (n > 58,000) and blood iodine. …”
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Machine Learning-Based Diabetes Risk Prediction Using Associated Behavioral Features by Ayodeji O. J. Ibitoye, Joseph D. Akinyemi, Olufade F. W. Onifade

“…In this work, we explored feature importance and correlation to derive the top 15 feature pairs from a dataset of 263,882 samples of anonymized patient information. …”
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The association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and sarcopenia: A cross-sectional study by Xiudeng Yang, Zheng Zhong

“…Methods: Data on NHHR and sarcopenia were based on the secondary analysis of the years 2011–2018 of National Health and Nutrition Examination Survey (NHANES) dataset. NHHR was nature log-transformed (LnNHHR) to achieve a normal distribution. …”
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Effectiveness of fractionated microneedle radiofrequency in treatment of seborrheic dermatitis by Anwar Issa Hasan, Ethar Falah Hasan, Tuqa Mohammed Latif

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A Lightweight Network with Domain Adaptation for Motor Imagery Recognition by Xinmin Ding, Zenghui Zhang, Kun Wang, Xiaolin Xiao, Minpeng Xu

“…The proposed method was evaluated on an fNIRS motor imagery dataset, achieving an average accuracy of 87.76% in a three-class classification task. …”
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Trust in Intrusion Detection Systems: An Investigation of Performance Analysis for Machine Learning and Deep Learning Models by Basim Mahbooba, Radhya Sahal, Wael Alosaimi, Martin Serrano

“…The four deep learning techniques are LSTM (one and two layers) and GRU (one and two layers). Two datasets are used to classify the IDS attack type, including wireless sensor network detection system (WSN-DS) and KDD Cup network intrusion dataset. …”
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Solution of Extraordinary Differential Equations with Physical Reasoning by Obtaining Modal Reaction Series by Shantanu Das

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Explainable correlation-based anomaly detection for Industrial Control Systems by Ermiyas Birihanu, Imre Lendák

“…The method is evaluated on the Secure Water Treatment (SWaT), Hardware-in-the-loop-based augmented ICS security (HIL-HAI), and Internet of Things Modbus dataset using precision, recall, and F-1 score metrics. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…The research utilizes a dataset consisting of 1,428 training samples and 573 testing samples, evaluated using a 10-fold cross-validation technique. …”
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A Multimodal Information Fusion Model for Robot Action Recognition with Time Series by Xiaozhi Zhang, Hongyan Li, Mengjie Qian

“…Experiment results on the publicly available datasets NTU-RGB + D and MSR Action 3D show that the method proposed in this paper can improve action recognition accuracy.…”
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