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521
Screening OSA in Chinese Smart Device Consumers: A Real-World Arrhythmia-Related Study
Published 2025-04-01“…Our previous study validated an algorithm-based photoplethysmography (PPG) smartwatch for OSA risk detection.Objective: This study aimed to characterize OSA features and assess its association with arrhythmia risk among smart wearable device (SWD) consumers in China in a real-world setting.Methods: Between December 15, 2019, and January 31, 2022, SWD consumers across China were screened for OSA risk using HUAWEI devices. …”
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522
Socially Responsible Investment Portfolio Construction with a Double-Screening Mechanism considering Machine Learning Prediction
Published 2021-01-01“…The proposed models consist of two stages, i.e., stock screening and asset allocation. …”
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523
Pulmonary Nodules Detection Algorithm Combining Multi-view and Attention Mechanism
Published 2022-12-01Get full text
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524
Efficient text-to-video retrieval via multi-modal multi-tagger derived pre-screening
Published 2025-03-01“…In this work, we present a plug-and-play multi-modal multi-tagger-driven pre-screening framework, which pre-screens a substantial number of videos before applying any TVR algorithms, thereby efficiently reducing the search space of videos. …”
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525
Preterm preeclampsia screening and prevention: a comprehensive approach to implementation in a real-world setting
Published 2025-01-01“…Abstract Background Preeclampsia significantly impacts maternal and perinatal health. Early screening using advanced models and primary prevention with low-dose acetylsalicylic acid for high-risk populations is crucial to reduce the disease’s incidence. …”
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526
Panel defect detection algorithm based on improved Faster R-CNN
Published 2022-01-01“…Experimental results show that the accuracy and recognition rate of the optimized network model have been greatly improved.…”
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527
A Hybrid Artificial Intelligence Approach for Down Syndrome Risk Prediction in First Trimester Screening
Published 2025-06-01“…<b>Background/Objectives:</b> The aim of this study is to develop a hybrid artificial intelligence (AI) approach to improve the accuracy, efficiency, and reliability of Down Syndrome (DS) risk prediction during first trimester prenatal screening. The proposed method transforms one-dimensional (1D) patient data—including features such as nuchal translucency (NT), human chorionic gonadotropin (hCG), and pregnancy-associated plasma protein A (PAPP-A)—into two-dimensional (2D) Aztec barcode images, enabling advanced feature extraction using transformer-based deep learning models. …”
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528
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529
Creating a retinal image database to develop an automated screening tool for diabetic retinopathy in India
Published 2025-03-01“…Our work is expected to mark a significant stride in DR detection and management, promising a more efficient and scalable solution for tackling this global health challenge.…”
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530
Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension
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531
Predicting algorithm of attC site based on combination optimization strategy
Published 2022-12-01“…Based on the structural features of attC sites, the prediction algorithm realises the high-precision prediction of the recombination frequencies between sites and the screening of the top 20 important features that play a role in recombination, which are effective for improving the design method of attC sites. …”
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532
MLP-UNet: an algorithm for segmenting lesions in breast and thyroid ultrasound images
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533
Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm
Published 2021-01-01“…In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated.…”
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534
Birdsong Recognition Based on Attention Hash Algorithm Combined with Contrastive Loss
Published 2024-12-01“…Aiming at the problems of length misalignment, redundancy, noise and large intra-class differences in birdsong data collected in the natural environment, an automatic birdsong recognition model composed of a two-stage hash algorithm based on multi- level attention and a lightweight classifier based on fusion contrastive loss is proposed. …”
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535
High-throughput screening and machine learning classification of van der Waals dielectrics for 2D nanoelectronics
Published 2024-11-01“…Here, we employed a topology-scale algorithm to screen vdW materials consisting of zero-dimensional (0D), one-dimensional (1D), and 2D motifs from Materials Project database. …”
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536
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537
Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening
Published 2025-05-01“…This study employed a quantitative structure–activity relationship (QSAR) model based on ECFP4 molecular fingerprints with several machine learning algorithms (XGBoost, RF, SVM, KNN), among which the XGBoost model showed the best performance (AUC = 0.9740). …”
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538
Cost-effectiveness of advanced hepatic fibrosis screening in individuals with suspected MASLD identified by serologic noninvasive tests
Published 2025-07-01“…We applied a decision tree and Markov model from a healthcare system perspective to estimate life-years, quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness ratio (ICER) for screening versus no screening in the United States. …”
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539
Prediction of hypertensive disorders in pregnant women in the «gray» risk zone following combined first-trimester screening
Published 2024-05-01“…Aim: to develop a prognostic model for risk stratification in female patients with borderline to high developing PE risk based on combined first-trimester screening. …”
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540
Identifying USP1 Inhibitors with Allosteric Effect on Its Triple Catalytic Center through Virtual Screening
Published 2023-01-01“…In this study, we performed virtual screening on a database containing about 1.37 million molecules using the pharmacophore model, multiple precision molecular docking algorithms, molecular mechanics/generalized born surface area (MM/GBSA), strain energy, and ADMET screening methods. …”
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