AIMC Topic: Reproducibility of Results

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Quantitative Assessment of Resting-State for Mild Cognitive Impairment Detection: A Functional Near-Infrared Spectroscopy and Deep Learning Approach.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease. Early diagnosis of MCI can allow for treatment to improve cognitive function and reduce modifiable risk factors.
Neural Pathways Spectroscopy, Near-Infrared Deep Learning Cognitive Dysfunction Support Vector Machine Brain Mapping Humans Discriminant Analysis Female Neural Networks, Computer Feasibility Studies Reproducibility of Results Machine Learning Rest Aged Neuroimaging Aged, 80 and over Algorithms Male
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Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cos...
Apolipoproteins E Mental Recall Positron-Emission Tomography Hippocampus Cerebral Cortex Cohort Studies Female Neuropsychological Tests Humans Magnetic Resonance Imaging Reproducibility of Results Machine Learning Risk Factors Male Predictive Value of Tests Algorithms Aged Middle Aged Aged, 80 and over Disease Progression Area Under Curve Cognitive Dysfunction Amyloid beta-Peptides
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COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader.

Journal of X-ray science and technology Jan 1, 2021
BACKGROUND: Chest X-ray imaging has been proved as a powerful diagnostic method to detect and diagnose COVID-19 cases due to its easy accessibility, lower cost and rapid imaging time.
Algorithms Tomography, X-Ray Computed Reproducibility of Results SARS-CoV-2 Deep Learning Pneumonia Early Diagnosis Radiography, Thoracic Humans Neural Networks, Computer COVID-19
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Deep learning model for the prediction of microsatellite instability in colorectal cancer: a diagnostic study.

The Lancet. Oncology Jan 1, 2021
BACKGROUND: Detecting microsatellite instability (MSI) in colorectal cancer is crucial for clinical decision making, as it identifies patients with differential treatment response and prognosis. Universal MSI testing is recommended, but many patients...
Coloring Agents Deep Learning Microscopy Hematoxylin Humans Genetic Predisposition to Disease Image Interpretation, Computer-Assisted Phenotype Staining and Labeling Eosine Yellowish-(YS) Reproducibility of Results Predictive Value of Tests Colorectal Neoplasms Microsatellite Instability Diagnosis, Computer-Assisted
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Improved SSD network for accurate detection of optic disc and fovea and application in excyclotropia screening.

Journal of the Optical Society of America. A, Optics, image science, and vision Jan 1, 2021
The detection of the optic disc (OD) and fovea is essential to many automatic diagnosis systems for retinal diseases. The single shot multibox detector (SSD) can generate predictions from feature maps of various resolutions, which has not been introd...
Pattern Recognition, Automated Fovea Centralis Exotropia Reproducibility of Results Sensitivity and Specificity Image Interpretation, Computer-Assisted Optic Disk Humans Neural Networks, Computer Algorithms Databases, Factual
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Toward Improved and Standardized Diagnostic Pipelines in Transplantation.

Transplantation Jan 1, 2021
Observer Variation Reproducibility of Results Diagnosis, Computer-Assisted Molecular Diagnostic Techniques Treatment Outcome Predictive Value of Tests Graft Rejection Organ Transplantation Biopsy Workflow Humans Machine Learning
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Construction of MRI-Based Alzheimer's Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset.

Journal of Alzheimer's disease : JAD Jan 1, 2021
BACKGROUND: In recent years, many convolutional neural networks (CNN) have been proposed for the classification of Alzheimer's disease. Due to memory constraints, many of the proposed CNNs work at a 2D slice-level or 3D patch-level.
Reproducibility of Results Cognitive Dysfunction Imaging, Three-Dimensional Magnetic Resonance Imaging Alzheimer Disease Humans Neural Networks, Computer Brain
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Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: comparison with expert subjective assessment.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Jan 1, 2021
OBJECTIVES: To develop and test the performance of computerized ultrasound image analysis using deep neural networks (DNNs) in discriminating between benign and malignant ovarian tumors and to compare its diagnostic accuracy with that of subjective a...
Sensitivity and Specificity Deep Learning Image Processing, Computer-Assisted Diagnosis, Differential Ovarian Neoplasms Humans Retrospective Studies Female Reproducibility of Results Ultrasonography, Doppler Adnexal Diseases
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Development of Machine Learning Models for Predicting Postoperative Delayed Remission in Patients With Cushing's Disease.

The Journal of clinical endocrinology and metabolism Jan 1, 2021
CONTEXT: Postoperative hypercortisolemia mandates further therapy in patients with Cushing's disease (CD). Delayed remission (DR) is defined as not achieving postoperative immediate remission (IR), but having spontaneous remission during long-term fo...
Postoperative Period Pituitary ACTH Hypersecretion ACTH-Secreting Pituitary Adenoma Models, Statistical Adenoma Neurosurgical Procedures Remission Induction Reproducibility of Results Algorithms Middle Aged Young Adult Humans Computer Simulation China Adult Machine Learning Prognosis Time Factors Male Retrospective Studies Treatment Outcome Female Follow-Up Studies
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Big Data Analytics + Virtual Clinical Semantic Network (vCSN): An Approach to Addressing the Increasing Clinical Nuances and Organ Involvement of COVID-19.

ASAIO journal (American Society for Artificial Internal Organs : 1992) Jan 1, 2021
The coronavirus disease 2019 (COVID-19) pandemic has revealed deep gaps in our understanding of the clinical nuances of this extremely infectious viral pathogen. In order for public health, care delivery systems, clinicians, and other stakeholders to...
Humans Artificial Intelligence Models, Theoretical Medical Informatics Semantics Symptom Assessment Semantic Web Machine Learning COVID-19 Reproducibility of Results Big Data Data Science
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