Medicare

A White-Box Testing for Deep Neural Networks Based on Neuron Coverage.

With the introduction of neuron coverage as a testing criterion for deep neural networks (DNNs), cov...

Chart Review Is Dead; Long Live Chart Review: How Artificial Intelligence Will Make Human Review of Medical Records Obsolete, One Day.

Surgical scheduling via optimization and machine learning with long-tailed data : Health care management science, in press.

Using data from cardiovascular surgery patients with long and highly variable post-surgical lengths ...

Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.

Objective analysis of rotator cuff (RC) atrophy and fatty infiltration (FI) from clinical MRI is lim...

Robotic self-modulation enhances implantable long-acting drug delivery devices.

Integrating fibrotic capsule sensing with soft robotics may boost long-term performance of implantab...

Sex estimation from long bones: a machine learning approach.

Sex estimation from skeletal remains is one of the crucial issues in forensic anthropology. Long bon...

Super-resolution of magnetic resonance images using Generative Adversarial Networks.

Magnetic Resonance Imaging (MRI) typically comes at the cost of small spatial coverage, high expense...

[Robot-assisted visceral surgery in Germany : Analysis of the current status and trends of the last 5 years using data from the StuDoQ|Robotics registry].

Robot-assisted systems have been increasingly used in general surgery for several years. Accordingly...

Developing a model to explain users' ethical perceptions regarding the use of care robots in home care: A cross-sectional study in Ireland, Finland, and Japan.

To date, research on ethical issues regarding care robots for older adults, family caregivers, and c...

A deep-learning assisted bioluminescence tomography method to enable radiation targeting in rat glioblastoma.

. A novel solution is required for accurate 3D bioluminescence tomography (BLT) based glioblastoma (...

Prediction sets adaptive to unknown covariate shift.

Predicting sets of outcomes-instead of unique outcomes-is a promising solution to uncertainty quanti...

Rm-LR: A long-range-based deep learning model for predicting multiple types of RNA modifications.

Recent research has highlighted the pivotal role of RNA post-transcriptional modifications in the re...

Automated Natural Language Processing-Based Supplier Discovery for Financial Services.

Public procurement is viewed as a major market force that can be used to promote innovation and driv...

Localizing in-domain adaptation of transformer-based biomedical language models.

In the era of digital healthcare, the huge volumes of textual information generated every day in hos...

Computed Tomography 2.0: New Detector Technology, AI, and Other Developments.

Computed tomography (CT) dramatically improved the capabilities of diagnostic and interventional rad...

Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue.

While some robust artificial intelligence (AI) techniques such as Gene-Expression Programming (GEP),...

Sensor Topology Optimization in Dense IoT Environments by Applying Neural Network Configuration.

In dense IoT deployments of wireless sensor networks (WSNs), sensor placement, coverage, connectivit...

Lite-SeqCNN: A Light-Weight Deep CNN Architecture for Protein Function Prediction.

The short-and-long range interactions amongst amino-acids in a protein sequence are primarily respon...

Body height estimation from automated length measurements on standing long leg radiographs using artificial intelligence.

Artificial-intelligence (AI) allows large-scale analyses of long-leg-radiographs (LLRs). We used thi...

Reconstructive Allograft Preparation for Long Bone Intercalary Segments After Tumor Resections: Toronto Sarcoma Protocol.

BACKGROUND: The Reconstructive Allograft Preparation by Toronto Sarcoma (RAPTORS) protocol is reliab...

SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data.

BACKGROUND: Structural variations (SVs) refer to variations in an organism's chromosome structure th...