AIMC Topic: ROC Curve

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Application of a deep learning system in glaucoma screening and further classification with colour fundus photographs: a case control study.

BMC ophthalmology Dec 12, 2022
BACKGROUND: To verify efficacy of automatic screening and classification of glaucoma with deep learning system.
Cross-Sectional Studies Case-Control Studies Glaucoma Retrospective Studies Fundus Oculi Optic Disk Deep Learning ROC Curve Humans
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Using artificial intelligence in a primary care setting to identify patients at risk for cancer: a risk prediction model based on routine laboratory tests.

Clinical chemistry and laboratory medicine Nov 30, 2022
OBJECTIVES: To evaluate the ability of an artificial intelligence (AI) model to predict the risk of cancer in patients referred from primary care based on routine blood tests. Results obtained with the AI model are compared to results based on logist...
Neoplasms ROC Curve Primary Health Care Humans Artificial Intelligence Sensitivity and Specificity
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Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models.

Journal of clinical epidemiology Nov 25, 2022
BACKGROUND AND OBJECTIVES: We sought to summarize the study design, modelling strategies, and performance measures reported in studies on clinical prediction models developed using machine learning techniques.
Supervised Machine Learning ROC Curve Humans Algorithms Machine Learning Prognosis
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Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach.

Sensors (Basel, Switzerland) Nov 25, 2022
Slope failures lead to large casualties and catastrophic societal and economic consequences, thus potentially threatening access to sustainable development. Slope stability assessment, offering potential long-term benefits for sustainable development...
Humans Machine Learning ROC Curve Algorithms Friction Databases, Factual
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An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective study.

Breast cancer research : BCR Nov 21, 2022
BACKGROUND: The biological phenotype of tumours evolves during neoadjuvant chemotherapy (NAC). Accurate prediction of pathological complete response (pCR) to NAC in the early-stage or posttreatment can optimize treatment strategies or improve the bre...
Neoadjuvant Therapy Retrospective Studies Neoplasms Ultrasonography Deep Learning ROC Curve
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A Deep Learning Approach to Detect Anomalies in an Electric Power Steering System.

Sensors (Basel, Switzerland) Nov 20, 2022
As anomaly detection for electrical power steering (EPS) systems has been centralized using model- and knowledge-based approaches, EPS system have become complex and more sophisticated, thereby requiring enhanced reliability and safety. Since most cu...
Deep Learning ROC Curve Electricity Reproducibility of Results
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RGN: Residue-Based Graph Attention and Convolutional Network for Protein-Protein Interaction Site Prediction.

Journal of chemical information and modeling Nov 18, 2022
The prediction of a protein-protein interaction site (PPI site) plays a very important role in the biochemical process, and lots of computational methods have been proposed in the past. However, the majority of the past methods are time consuming and...
Amino Acids Proteins Neural Networks, Computer Algorithms ROC Curve
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A machine learning method for predicting the probability of MODS using only non-invasive parameters.

Computer methods and programs in biomedicine Nov 8, 2022
OBJECTIVES: Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essential for the rescue and treatment of trauma patients However, existing methods are invasive, easily affected by artifacts and can be difficult to perform...
Probability Machine Learning Databases, Factual ROC Curve Multiple Organ Failure Humans
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Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

BMC bioinformatics Nov 8, 2022
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to ...
Neural Networks, Computer Machine Learning Humans Receptors, Antigen, T-Cell Attention Neoplasms ROC Curve
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Finger Vein Verification on Different Datasets Based on Deep Learning with Triplet Loss.

Computational and mathematical methods in medicine Oct 20, 2022
In this study, deep learning and triplet loss function methods are used for finger vein verification research, and the model is trained and validated between different kinds of datasets including FV-USM, HKPU, and SDUMLA-HMT datasets. This work gives...
Veins Humans Deep Learning ROC Curve
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