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Data Accuracy

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Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.

Accurate Prediction for Antibody Resistance of Clinical HIV-1 Isolates.

Scientific reports
Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection, and several are currently undergoing clinical trials. Due to the high sequence diversity an...

Ambient virtual scribes: Mutuo Health's AutoScribe as a case study of artificial intelligence-based technology.

Healthcare management forum
Studies show that clinicians are increasingly burning out in large part from the clerical burden associated with using Electronic Medical Record (EMR) systems. At the same time, recently developed health data analytic algorithms struggle with poor qu...

nanite: using machine learning to assess the quality of atomic force microscopy-enabled nano-indentation data.

BMC bioinformatics
BACKGROUND: Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when dealing with biological tissue is ...

His-GAN: A histogram-based GAN model to improve data generation quality.

Neural networks : the official journal of the International Neural Network Society
Generative Adversarial Network (GAN) has become an active research field due to its capability to generate quality simulation data. However, two consistent distributions (generated data distribution and original data distribution) produced by GAN can...

Efficient training of interval Neural Networks for imprecise training data.

Neural networks : the official journal of the International Neural Network Society
This paper describes a robust and computationally feasible method to train and quantify the uncertainty of Neural Networks. Specifically, we propose a back propagation algorithm for Neural Networks with interval predictions. In order to maintain nume...

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

Nutrients
BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research out...

Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases.

Health information management : journal of the Health Information Management Association of Australia
BACKGROUND: The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basic DRG structure by incorporating four severity of illness (SOI) levels, which are used for determining hospital payment. A comprehensive report of all...