AIMC Topic:
ROC Curve

Clear Filters Showing 2111 to 2120 of 3214 articles

Highly accelerated, model-free diffusion tensor MRI reconstruction using neural networks.

Medical physics
PURPOSE: The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans.

An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA) or 4-archetype (4AA) unsupervised algorithms to estimate rejection. In the present study we ex...

An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...

Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

Ophthalmology. Retina
PURPOSE: Accurate image-based ophthalmic diagnosis relies on fundus image clarity. This has important implications for the quality of ophthalmic diagnoses and for emerging methods such as telemedicine and computer-based image analysis. The purpose of...

Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.

Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks.

International journal of environmental research and public health
Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place in prevalence worldwide. Early diabetes detection has become important to prevent other health condit...

Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters.

Journal of chemical information and modeling
Assay interference caused by small molecules continues to pose a significant challenge for early drug discovery. A number of rule-based and similarity-based approaches have been derived that allow the flagging of potentially "badly behaving compounds...

tRNA-DL: A Deep Learning Approach to Improve tRNAscan-SE Prediction Results.

Human heredity
BACKGROUND: tRNAscan-SE is the leading tool for transfer RNA (tRNA) annotation, which has been widely used in the field. However, tRNAscan-SE can return a significant number of false positives when applied to large sequences. Recently, conventional m...

Dermoscopy diagnosis of cancerous lesions utilizing dual deep learning algorithms via visual and audio (sonification) outputs: Laboratory and prospective observational studies.

EBioMedicine
BACKGROUND: Early diagnosis of skin cancer lesions by dermoscopy, the gold standard in dermatological imaging, calls for a diagnostic upscale. The aim of the study was to improve the accuracy of dermoscopic skin cancer diagnosis through use of novel ...