AIMC Topic: Predictive Value of Tests

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Survival prognostic factors in patients with acute myeloid leukemia using machine learning techniques.

PloS one Jul 21, 2021
This paper identifies prognosis factors for survival in patients with acute myeloid leukemia (AML) using machine learning techniques. We have integrated machine learning with feature selection methods and have compared their performances to identify ...
Survival Rate Leukemia, Myeloid, Acute Male Middle Aged Risk Factors Aged Aged, 80 and over Adult Humans Machine Learning Female Adolescent Predictive Value of Tests Models, Biological Disease-Free Survival
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A Machine Learning Tool Using Digital Microscopy (Morphogo) for the Identification of Abnormal Lymphocytes in the Bone Marrow.

Acta cytologica Jul 20, 2021
Morphological analysis of the bone marrow is an essential step in the diagnosis of hematological disease. The conventional analysis of bone marrow smears is performed under a manual microscope, which is labor-intensive and subject to interobserver va...
Lymphocytes Bone Marrow Cells Reproducibility of Results Microscopy Bone Marrow Examination Humans Image Interpretation, Computer-Assisted Diagnosis, Computer-Assisted Machine Learning Lymphoma Retrospective Studies Predictive Value of Tests
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Quick Annotator: an open-source digital pathology based rapid image annotation tool.

The journal of pathology. Clinical research Jul 19, 2021
Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest...
High-Throughput Screening Assays Image Interpretation, Computer-Assisted Cell Nucleus Pathology Predictive Value of Tests Biopsy Workflow Microscopy Humans Deep Learning Automation, Laboratory Time Factors Reproducibility of Results Epithelial Cells Colorectal Neoplasms
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Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.

Virchows Archiv : an international journal of pathology Jul 19, 2021
The level of human epidermal growth factor receptor-2 (HER2) protein and gene expression in breast cancer is an essential factor in judging the prognosis of breast cancer patients. Several investigations have shown high intraobserver and interobserve...
Predictive Value of Tests Microscopy In Situ Hybridization, Fluorescence Image Interpretation, Computer-Assisted Observer Variation Immunohistochemistry Humans Receptor, ErbB-2 Artificial Intelligence Carcinoma, Ductal, Breast Reproducibility of Results Automation, Laboratory Breast Neoplasms Biomarkers, Tumor Retrospective Studies China Female
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Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling.

Scientific reports Jul 19, 2021
For a patient affected by breast cancer, after tumor removal, it is necessary to decide which adjuvant therapy is able to prevent tumor relapse and formation of metastases. A prediction of the outcome of adjuvant therapy tailored for the patient is h...
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Predictive Value of Tests Mastectomy Neoplasm Recurrence, Local Gene Expression Profiling Survival Analysis Transcriptome Gene Regulatory Networks Gene Expression Regulation, Neoplastic Microarray Analysis Prognosis Chemotherapy, Adjuvant Female Breast Neoplasms Biomarkers, Tumor
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Systematic Quantification of Sources of Variation in Ejection Fraction Calculation Using Deep Learning.

JACC. Cardiovascular imaging Jul 14, 2021
Deep Learning Predictive Value of Tests Humans Ventricular Function, Left Stroke Volume Echocardiography
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Can Machine Learning Help Simplify the Measurement of Diastolic Function in Echocardiography?

JACC. Cardiovascular imaging Jul 14, 2021
Humans Machine Learning Echocardiography Predictive Value of Tests Diastole
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Phenogrouping Diastolic Dysfunction by Artificial Intelligence: Learning From What We Teach the Machines.

JACC. Cardiovascular imaging Jul 14, 2021
Artificial Intelligence Machine Learning Algorithms Predictive Value of Tests Humans Cardiomyopathies
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Predicting survival in heart failure: a risk score based on machine-learning and change point algorithm.

Clinical research in cardiology : official journal of the German Cardiac Society Jul 14, 2021
OBJECTIVE: Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with ...
Male Middle Aged Registries Republic of Korea Risk Assessment Heart Failure Female Predictive Value of Tests Humans Aged Machine Learning Survival Rate Prognosis
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CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

Stroke Jul 9, 2021
BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and appl...
Young Adult Adult Male Middle Aged Prognosis Female Reproducibility of Results Aged Models, Statistical Predictive Value of Tests C-Reactive Protein Subarachnoid Hemorrhage ROC Curve Logistic Models Treatment Outcome Support Vector Machine Humans Machine Learning
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