AIMC Topic: ROC Curve

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Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images.

Ophthalmology. Retina Jan 26, 2024
OBJECTIVE: We aimed to develop a deep learning system capable of identifying subjects with cognitive impairment quickly and easily based on multimodal ocular images.
Tomography, Optical Coherence Humans Retrospective Studies Aged Fundus Oculi Female Cross-Sectional Studies Middle Aged Optic Disk Male ROC Curve Deep Learning Mass Screening Cognitive Dysfunction Multimodal Imaging
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Screening of Moyamoya Disease From Retinal Photographs: Development and Validation of Deep Learning Algorithms.

Stroke Jan 23, 2024
BACKGROUND: Moyamoya disease (MMD) is a rare and complex pathological condition characterized by an abnormal collateral circulation network in the basal brain. The diagnosis of MMD and its progression is unpredictable and influenced by many factors. ...
Deep Learning ROC Curve Moyamoya Disease Humans Algorithms Adult
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Evaluating deep learning-based melanoma classification using immunohistochemistry and routine histology: A three center study.

PloS one Jan 19, 2024
Pathologists routinely use immunohistochemical (IHC)-stained tissue slides against MelanA in addition to hematoxylin and eosin (H&E)-stained slides to improve their accuracy in diagnosing melanomas. The use of diagnostic Deep Learning (DL)-based supp...
Humans Melanoma MART-1 Antigen Deep Learning ROC Curve Immunohistochemistry
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Enhancing Nigrosome-1 Sign Identification via Interpretable AI using True Susceptibility Weighted Imaging.

Journal of magnetic resonance imaging : JMRI Jan 18, 2024
BACKGROUND: Nigrosome 1 (N1), the largest nigrosome region in the ventrolateral area of the substantia nigra pars compacta, is identifiable by the "N1 sign" in long echo time gradient echo MRI. The N1 sign's absence is a vital Parkinson's disease (PD...
Female Reproducibility of Results Aged Humans Prospective Studies Deep Learning ROC Curve Magnetic Resonance Imaging Parkinson Disease Adult Male Middle Aged Image Interpretation, Computer-Assisted Substantia Nigra
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Image Analysis-Based Machine Learning for the Diagnosis of Retinopathy of Prematurity: A Meta-analysis and Systematic Review.

Ophthalmology. Retina Jan 17, 2024
TOPIC: To evaluate the performance of machine learning (ML) in the diagnosis of retinopathy of prematurity (ROP) and to assess whether it can be an effective automated diagnostic tool for clinical applications.
Infant, Newborn Humans Retinopathy of Prematurity ROC Curve Machine Learning Image Processing, Computer-Assisted
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A Machine Learning Approach to Predict Post-stroke Fatigue. The Nor-COAST study.

Archives of physical medicine and rehabilitation Jan 17, 2024
OBJECTIVE: This study aimed to predict fatigue 18 months post-stroke by utilizing comprehensive data from the acute and sub-acute phases after stroke in a machine-learning set-up.
Middle Aged ROC Curve Stroke Fatigue Stroke Rehabilitation Aged Aged, 80 and over Humans Male Machine Learning Prospective Studies Female
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Machine learning methods for developing a predictive model of the incidence of delirium in cardiac intensive care units.

Revista espanola de cardiologia (English ed.) Jan 16, 2024
INTRODUCTION AND OBJECTIVES: Delirium, recognized as a crucial prognostic factor in the cardiac intensive care unit (CICU), has evolved in response to the changing demographics among critically ill cardiac patients. This study aimed to create a predi...
Coronary Care Units Male Middle Aged Risk Assessment Incidence ROC Curve Delirium Female Risk Factors Aged Retrospective Studies Critical Illness Intensive Care Units Machine Learning Prognosis Humans
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MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

Journal of magnetic resonance imaging : JMRI Jan 11, 2024
BACKGROUND: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC...
Breast Neoplasms Middle Aged Deep Learning Reproducibility of Results Aged Adult Contrast Media Magnetic Resonance Imaging Axilla Kinetics ROC Curve Lymph Nodes Lymphatic Metastasis Retrospective Studies Humans Female Neural Networks, Computer
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Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study.

The Lancet. Digital health Jan 11, 2024
BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy. Timely diagnosis of ovarian cancer is difficult due to the lack of effective biomarkers. Laboratory tests are widely applied in clinical practice, and some have shown diagnostic ...
Female ROC Curve Ovarian Neoplasms Artificial Intelligence Prognosis Humans Retrospective Studies
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Applicability Area: A novel utility-based approach for evaluating predictive models, beyond discrimination.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
Translating prediction models into practice and supporting clinicians' decision-making demand demonstration of clinical value. Existing approaches to evaluating machine learning models emphasize discriminatory power, which is only a part of the medic...
Humans Machine Learning ROC Curve
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