AIMC Topic: Prognosis

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Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society May 2, 2019
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...
Humans Neural Networks, Computer Research Design Prognosis Tomography, X-Ray Computed Deep Learning Child Cystic Fibrosis Pediatrics Radiography, Thoracic Female Reproducibility of Results Male Lung Severity of Illness Index
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A deep learning radiomics model for preoperative grading in meningioma.

European journal of radiology May 1, 2019
OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model based on routine post-contrast MRI.
Neoplasm Grading Preoperative Care Meningioma Meningeal Neoplasms Meninges Prognosis Humans Young Adult Retrospective Studies Algorithms Deep Learning Adult Female Adolescent Reproducibility of Results Sensitivity and Specificity Cohort Studies Male Aged Magnetic Resonance Imaging Middle Aged Area Under Curve
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Beyond multidrug resistance: Leveraging rare variants with machine and statistical learning models in Mycobacterium tuberculosis resistance prediction.

EBioMedicine Apr 29, 2019
BACKGROUND: The diagnosis of multidrug resistant and extensively drug resistant tuberculosis is a global health priority. Whole genome sequencing of clinical Mycobacterium tuberculosis isolates promises to circumvent the long wait times and limited s...
Mycobacterium tuberculosis Genome, Bacterial Extensively Drug-Resistant Tuberculosis Models, Statistical Evolution, Molecular ROC Curve Humans Antitubercular Agents Genomics Machine Learning Tuberculosis, Multidrug-Resistant Computational Biology Prognosis Genetic Variation Databases, Genetic Reproducibility of Results Cluster Analysis Microbial Sensitivity Tests
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Towards interpretable machine learning models for diagnosis aid: A case study on attention deficit/hyperactivity disorder.

PloS one Apr 25, 2019
Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that has heavy consequences on a child's wellbeing, especially in the academic, psychological and relational planes. The current evaluation of the disorder is supported ...
Diagnostic and Statistical Manual of Mental Disorders Attention Deficit Disorder with Hyperactivity Limbic System Diagnosis, Computer-Assisted Adolescent Child Decision Trees Datasets as Topic Humans Machine Learning Prognosis Female Male
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Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research Apr 22, 2019
PURPOSE: Tumors are continuously evolving biological systems, and medical imaging is uniquely positioned to monitor changes throughout treatment. Although qualitatively tracking lesions over space and time may be trivial, the development of clinicall...
Carcinoma, Non-Small-Cell Lung Neoplasm Staging Positron-Emission Tomography Neoplasm Metastasis Kaplan-Meier Estimate Deep Learning Time Factors Image Processing, Computer-Assisted Lung Neoplasms Treatment Outcome Humans Neural Networks, Computer Algorithms Prognosis Tomography, X-Ray Computed
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Predicting childhood obesity using electronic health records and publicly available data.

PloS one Apr 22, 2019
BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities, and the difficulty in decreasing body mass index (BMI) later in life, effective strategies are needed to address this condition in early childhood. ...
ROC Curve Logistic Models Pediatric Obesity Body Mass Index Longitudinal Studies Humans Adult Machine Learning Male Adolescent Prognosis Child, Preschool Retrospective Studies Child Electronic Health Records Female Risk Factors
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Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning.

Journal of cardiovascular computed tomography Apr 21, 2019
In the last decade, technical advances in the field of medical imaging significantly improved and broadened the application of coronary CT angiography (CCTA) for the non-invasive assessment of coronary artery disease. Recently, similar breakthroughs ...
Reproducibility of Results Severity of Illness Index Deep Learning Predictive Value of Tests Humans Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Prognosis Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography
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Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

Journal of cellular and molecular medicine Apr 18, 2019
BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival outcome and associations with differentially expressed Genes (RNA Sequencing) in groups of glioblastoma multiforme (GBM) patients.
Transcriptome Adolescent ROC Curve Genomics Gene Expression Regulation, Neoplastic Magnetic Resonance Imaging Glioblastoma Radiographic Image Interpretation, Computer-Assisted Biomarkers, Tumor Brain Neoplasms Male Middle Aged Gene Expression Profiling Aged Aged, 80 and over Young Adult Adult Survival Rate Humans Machine Learning Algorithms Prognosis Female
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Predictive Estimates of Risks Associated with Type 2 Diabetes Mellitus on the Basis of Biochemical Biomarkers and Derived Time-Dependent Parameters.

Journal of computational biology : a journal of computational molecular cell biology Apr 17, 2019
Risk Assessment Big Data Blood Glucose Diabetes Mellitus, Type 2 Cholesterol Biomarkers Prognosis Female Risk Factors Male Alanine Transaminase Aspartate Aminotransferases Humans Machine Learning
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Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer.

Cellular oncology (Dordrecht, Netherlands) Apr 15, 2019
PURPOSE: The prognostic value of mitotic count for invasive breast cancer is firmly established. As yet, however, limited studies have been aimed at assessing mitotic counts as a prognostic factor for triple negative breast cancers (TNBC). Here, we a...
Female Middle Aged Deep Learning Triple Negative Breast Neoplasms Disease-Free Survival Humans Algorithms Prognosis Proportional Hazards Models Multivariate Analysis Mitosis
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