AIMC Topic: Reproducibility of Results

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Two machine learning methods identify a metastasis-related prognostic model that predicts overall survival in medulloblastoma patients.

Aging Nov 5, 2020
Approximately 30% of medulloblastoma (MB) patients exhibit metastasis at initial diagnosis, which often leads to a poor prognosis. Here, by using univariate Cox regression analysis, two machine learning methods (Lasso-penalized Cox regression and ran...
Cerebellar Neoplasms Medulloblastoma Humans Machine Learning Decision Support Techniques Prognosis Clinical Decision-Making Female Infant Gene Expression Profiling Transcriptome Adolescent Nomograms Databases, Genetic Predictive Value of Tests Child, Preschool Child Biomarkers, Tumor Male Middle Aged Risk Assessment Reproducibility of Results Risk Factors Young Adult Adult
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Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research Nov 4, 2020
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...
Male ROC Curve Lung Neoplasms Adenocarcinoma Carcinoma, Non-Small-Cell Lung Area Under Curve Mutation ErbB Receptors Algorithms Tomography, X-Ray Computed Female Reproducibility of Results Humans Machine Learning
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Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.

European journal of radiology Nov 4, 2020
INTRODUCTION: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and ...
ROC Curve Male Radiographic Image Interpretation, Computer-Assisted Middle Aged Lung Tomography, X-Ray Computed Humans Deep Learning Female COVID-19 Reproducibility of Results Sensitivity and Specificity
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Application of deep neural techniques in predictive modelling for the estimation of Escherichia coli growth rate.

Journal of applied microbiology Nov 3, 2020
AIMS: To develop a predictive model for Escherichia coli using deep neural networks.
Temperature Neural Networks, Computer Reproducibility of Results Escherichia coli Models, Biological Food-Processing Industry
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Deep Learning for Detecting Cerebral Aneurysms with CT Angiography.

Radiology Nov 3, 2020
Background Cerebral aneurysm detection is a challenging task. Deep learning may become a supportive tool for more accurate interpretation. Purpose To develop a highly sensitive deep learning-based algorithm that assists in the detection of cerebral a...
Humans Retrospective Studies Middle Aged Deep Learning Image Interpretation, Computer-Assisted Computed Tomography Angiography Female Reproducibility of Results Sensitivity and Specificity Male Intracranial Aneurysm
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Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review.

Journal of medical Internet research Nov 3, 2020
BACKGROUND: Machine learning applications in health care have increased considerably in the recent past, and this review focuses on an important application in psychiatry related to the detection of depression. Since the advent of computational psych...
Depression Electroencephalography Humans Machine Learning Psychiatry Reproducibility of Results
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DeepFRET, a software for rapid and automated single-molecule FRET data classification using deep learning.

eLife Nov 3, 2020
Single-molecule Förster Resonance energy transfer (smFRET) is an adaptable method for studying the structure and dynamics of biomolecules. The development of high throughput methodologies and the growth of commercial instrumentation have outpaced the...
Kinetics Molecular Dynamics Simulation Nanotechnology Markov Chains Fluorescence Resonance Energy Transfer Deep Learning False Positive Reactions Software User-Computer Interface Single Molecule Imaging Fluorescent Dyes Algorithms Normal Distribution Signal Processing, Computer-Assisted Reproducibility of Results
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Challenges Developing Deep Learning Algorithms in Cytology.

Acta cytologica Nov 2, 2020
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...
Deep Learning Predictive Value of Tests Cytodiagnosis Image Interpretation, Computer-Assisted Humans Automation, Laboratory Reproducibility of Results Diagnosis, Computer-Assisted Quality Indicators, Health Care Computer Security Pathology
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Evaluation of Deep Learning to Augment Image-Guided Radiotherapy for Head and Neck and Prostate Cancers.

JAMA network open Nov 2, 2020
IMPORTANCE: Personalized radiotherapy planning depends on high-quality delineation of target tumors and surrounding organs at risk (OARs). This process puts additional time burdens on oncologists and introduces variability among both experts and inst...
Head and Neck Neoplasms Aged Humans Observer Variation Prostatic Neoplasms Neural Networks, Computer Male Organs at Risk Radiotherapy, Intensity-Modulated Tomography, X-Ray Computed Middle Aged Quality Improvement Radiotherapy, Image-Guided Reproducibility of Results Deep Learning
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Development and Validation of a Deep Learning Model for Detection of Allergic Reactions Using Safety Event Reports Across Hospitals.

JAMA network open Nov 2, 2020
IMPORTANCE: Although critical to patient safety, health care-related allergic reactions are challenging to identify and monitor.
Aged Adult Cross-Sectional Studies Male Humans Algorithms Hypersensitivity Middle Aged Patient Safety Boston Diagnosis, Computer-Assisted Female Deep Learning Reproducibility of Results ROC Curve
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