AIMC Topic: Predictive Value of Tests

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Automated body composition analysis of clinically acquired computed tomography scans using neural networks.

Clinical nutrition (Edinburgh, Scotland) Jan 22, 2020
BACKGROUND & AIMS: The quantity and quality of skeletal muscle and adipose tissue is an important prognostic factor for clinical outcomes across several illnesses. Clinically acquired computed tomography (CT) scans are commonly used for quantificatio...
Radiographic Image Interpretation, Computer-Assisted Lumbar Vertebrae Humans Adiposity Neural Networks, Computer Automation North America Muscle, Skeletal Tomography, X-Ray Computed Adipose Tissue Female Male Predictive Value of Tests Reproducibility of Results Middle Aged Body Composition Aged Deep Learning Adult Europe Sarcopenia
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Discovering hidden information in biosignals from patients using artificial intelligence.

Korean journal of anesthesiology Jan 16, 2020
Biosignals such as electrocardiogram or photoplethysmogram are widely used for determining and monitoring the medical condition of patients. It was recently discovered that more information could be gathered from biosignals by applying artificial int...
Deep Learning Electrocardiography Predictive Value of Tests Humans Artificial Intelligence Diagnosis, Computer-Assisted
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Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research Jan 14, 2020
PURPOSE: With increasing incidence of renal mass, it is important to make a pretreatment differentiation between benign renal mass and malignant tumor. We aimed to develop a deep learning model that distinguishes benign renal tumors from renal cell c...
Deep Learning Adolescent Child, Preschool Child Magnetic Resonance Imaging Aged, 80 and over Young Adult Adult Male Middle Aged Diagnosis, Differential Predictive Value of Tests Kidney Neoplasms Carcinoma, Renal Cell Humans Neural Networks, Computer Algorithms Retrospective Studies Female Aged
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Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.

Journal of cardiovascular computed tomography Jan 13, 2020
BACKGROUND: Advances in image reconstruction are necessary to decrease radiation exposure from coronary CT angiography (CCTA) further, but iterative reconstruction has been shown to degrade image quality at high levels. Deep-learning image reconstruc...
Humans Retrospective Studies Female Reproducibility of Results Aged Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Predictive Value of Tests Coronary Vessels Coronary Angiography Computed Tomography Angiography Radiographic Image Interpretation, Computer-Assisted Registries Coronary Artery Disease Artifacts
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Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

Journal of critical care Jan 9, 2020
PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health r...
Epidemiologic Studies Pattern Recognition, Automated False Positive Reactions International Classification of Diseases Humans Middle Aged Incidence Shock, Septic Predictive Value of Tests Hospitalization Databases, Factual Natural Language Processing Young Adult Prospective Studies Adult Intensive Care Units Software Sensitivity and Specificity Electronic Health Records Female
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Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study.

The Lancet. Oncology Jan 8, 2020
BACKGROUND: An increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatm...
Artificial Intelligence Prospective Studies Reproducibility of Results Sweden Aged Humans Prostatic Neoplasms Male Neoplasm Grading Biopsy Middle Aged Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Predictive Value of Tests
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Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study.

The Lancet. Oncology Jan 8, 2020
BACKGROUND: The Gleason score is the strongest correlating predictor of recurrence for prostate cancer, but has substantial inter-observer variability, limiting its usefulness for individual patients. Specialised urological pathologists have greater ...
Automation, Laboratory Image Interpretation, Computer-Assisted Retrospective Studies Observer Variation Reproducibility of Results Male Diagnosis, Computer-Assisted Deep Learning Predictive Value of Tests Prostatic Neoplasms Humans Neoplasm Grading Biopsy
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Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression.

JAMA network open Jan 3, 2020
IMPORTANCE: Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment ...
Prognosis Female Reproducibility of Results Adult Sensitivity and Specificity Humans Machine Learning Biomarkers Support Vector Machine Predictive Value of Tests Electroencephalography Male Citalopram Antidepressive Agents, Second-Generation Middle Aged Depressive Disorder, Major Canada Treatment Outcome
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Will artificial intelligence change the job of the cardiac imaging specialist?

Archives of cardiovascular diseases Dec 30, 2019
Image Interpretation, Computer-Assisted Reproducibility of Results Humans Cardiac Imaging Techniques Artificial Intelligence Machine Learning Diagnosis, Computer-Assisted Forecasting Predictive Value of Tests Heart Diseases Diffusion of Innovation
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High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Cancer immunology research Dec 23, 2019
Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on estimation of MHC binding aff...
Data Mining Mutation, Missense Histocompatibility Antigens Class II Humans Software Cancer Vaccines Neural Networks, Computer Algorithms Antigens, Neoplasm Artificial Intelligence Neoplasms CD8-Positive T-Lymphocytes Protein Binding Predictive Value of Tests Computational Biology Histocompatibility Antigens Class I
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