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721
Self‐Learning e‐Skin Respirometer for Pulmonary Disease Detection
Published 2024-12-01Get full text
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722
Numerical Background-Oriented Schlieren for Phase Reconstruction and Its Potential Applications
Published 2025-06-01“…This framework integrates two stages: forward modeling, using ray tracing to simulate image degradation, and inverse processing, using optical flow and a conjugate gradient algorithm to extract displacements and reconstruct phase information. …”
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723
Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic...
Published 2023-07-01“…Machine learning (ML) algorithms have been used to accurately identify cephalometric landmarks and detect irregularities related to orthodontics and dentistry. …”
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724
A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort stud...
Published 2025-04-01“…We employed nine machine learning algorithms to construct predictive models for gastric ulcers over the next seven years (2011–2018, with 1482 samples) and the next three years (2014–2018, with 2659 samples). …”
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725
A Convolutional Neural Network Using Anterior Segment Photos for Infectious Keratitis Identification
Published 2025-01-01“…Our models can be used as a screening tool for non-ophthalmic health care providers and ophthalmologists for rapid provisional diagnosis of infectious keratitis.Keywords: infectious keratitis, cornea ulcer, keratitis, conventional neural network, deep learning algorithm…”
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726
LatentDE: latent-based directed evolution for protein sequence design
Published 2025-01-01“…To mitigate this extensive procedure, recent advancements in machine learning-guided methodologies center around the establishment of a surrogate sequence-function model. In this paper, we propose latent-based DE (LDE), an evolutionary algorithm designed to prioritize the exploration of high-fitness mutants in the latent space. …”
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727
Autoimmune gastritis detection from preprocessed endoscopy images using deep transfer learning and moth flame optimization
Published 2025-07-01“…Various stages in the DL tool comprise; (i) Image collection and resizing, (ii) image pre-processing using Entropy-function and Moth-Flame (MF) Algorithm, (iii) deep-features extraction using a chosen DL-model, (iv) feature optimization using MF algorithm and serial features concatenation, and (iv) classification and performance confirmation using five-fold cross-validation. …”
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729
Identification of Alzheimer’s disease biomarkers and their immune function characterization
Published 2024-06-01“…Material and methods Based on bulk RNA-seq (GSE122063 and GSE97760), we screened potential biomarkers for AD by differential expression analysis and machine learning algorithms. …”
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730
Evaluation of a 1-hour troponin algorithm for diagnosing myocardial infarction in high-risk patients admitted to a chest pain unit: the prospective FAST-MI cohort study
Published 2019-11-01“…This algorithm recommend by current guidelines was previously developed in cohorts with a prevalence of MI of less than 20%.Design Prospective cohort study from November 2015 until December 2016.Setting Dedicated chest pain unit of a single referral centre.Participants Consecutive patients with suspected MI were screened. …”
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731
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732
Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma
Published 2025-05-01“…We utilized a combination of 101 machine learning algorithms to analyze the TCGA-KIRC cohort and the GSE22541 KIRC patients, screening for cell death patterns closely associated with prognosis from 18 potential modes. …”
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733
Nomogram for predicting the severity of high-risk plaques in acute coronary syndrome
Published 2025-06-01Get full text
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734
Early gestational diabetes mellitus risk predictor using neural network with NearMiss
Published 2025-12-01Get full text
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735
Sparse Temporal Data-Driven SSA-CNN-LSTM-Based Fault Prediction of Electromechanical Equipment in Rail Transit Stations
Published 2024-09-01“…The experiments showed that the proposed prediction method improved the RMSE by 0.000699, the MAE by 0.00042, and the R2 index by 0.109779 when predicting the fault rate data of platform screen doors on all of the lines. When predicting the fault rate data of the screen doors on a single line, the performance of the model was better than that of the CNN-LSTM model optimized with the PSO algorithm.…”
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736
The taming of sociodigital anticipations: AI in the digital welfare state
Published 2025-05-01“…“Tamed” anticipations of advanced algorithms are rooted within challenging working conditions (insufficient resources and time for clients), reconfigurations of roles and agencies (administration of systems instead of supporting clients) and nested within transformations of techno-bureaucratic regimes (from street- over screen- to system-level bureaucracies), which they envision to rectify and repair. …”
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737
Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies
Published 2025-03-01“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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738
Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and exploration of its p...
Published 2025-03-01“…Next, we constructed a rat renal IRI model and explored the role of key genes in renal IRI. …”
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739
Examining the empathy levels of medical students using CHAID analysis
Published 2025-05-01“…Methods The study was conducted with 322 medical students from a public university in Turkey. A relational screening model was applied, using a “Personal Information Form” and an “Empathy Scale” to gather data. …”
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740
A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility
Published 2024-10-01“…The stacking ensemble machine-learning model outperformed those three baseline models. Notably, the accuracy of the hybrid OS–Stacking model is most promising, up to 97.1%. …”
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