AIMC Topic: Databases, Factual

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A two-dimensional feasibility study of deep learning-based feature detection and characterization directly from CT sinograms.

Medical physics
Machine Learning, especially deep learning, has been used in typical x-ray computed tomography (CT) applications, including image reconstruction, image enhancement, image domain feature detection and image domain feature characterization. To our know...

Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.

Journal of digital imaging
Remarkable progress has been made in image classification and segmentation, due to the recent study of deep convolutional neural networks (CNNs). To solve the similar problem of diagnostic lung nodule detection in low-dose computed tomography (CT) sc...

Development and Assessment of a Machine Learning Model to Help Predict Survival Among Patients With Oral Squamous Cell Carcinoma.

JAMA otolaryngology-- head & neck surgery
IMPORTANCE: Predicting survival of oral squamous cell carcinoma through the use of prediction modeling has been underused, and the development of prediction models would augment clinicians' ability to provide absolute risk estimates for individual pa...

Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.

Journal of digital imaging
Computer-aided diagnosis (CAD) has already been widely used in medical image processing. We recently make another trial to implement convolutional neural network (CNN) on the classification of pulmonary nodules of thoracic CT images. The biggest chal...

Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.

Journal of digital imaging
Ensuring correct radiograph view labeling is important for machine learning algorithm development and quality control of studies obtained from multiple facilities. The purpose of this study was to develop and test the performance of a deep convolutio...

Deep learning for clustering of multivariate clinical patient trajectories with missing values.

GigaScience
BACKGROUND: Precision medicine requires a stratification of patients by disease presentation that is sufficiently informative to allow for selecting treatments on a per-patient basis. For many diseases, such as neurological disorders, this stratifica...

Transparent Reporting on Research Using Unstructured Electronic Health Record Data to Generate 'Real World' Evidence of Comparative Effectiveness and Safety.

Drug safety
Research that makes secondary use of administrative and clinical healthcare databases is increasingly influential for regulatory, reimbursement, and other healthcare decision-making. Consequently, there are numerous guidance documents on reporting fo...

Development of a global infectious disease activity database using natural language processing, machine learning, and human expertise.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We assessed whether machine learning can be utilized to allow efficient extraction of infectious disease activity information from online media reports.