Hospital-Based Medicine

Risk Management

Latest AI and machine learning research in risk management for healthcare professionals.

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Transfer learning in deep neural network based under-sampled MR image reconstruction.

In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image recon...

FPGAN: Face de-identification method with generative adversarial networks for social robots.

In this paper, we propose a new face de-identification method based on generative adversarial networ...

Artificial intelligence in medicine creates real risk management and litigation issues.

The next step in the evolution of electronic medical record (EMR) use is the integration of artifici...

Noise reduction with cross-tracer and cross-protocol deep transfer learning for low-dose PET.

Previous studies have demonstrated the feasibility of reducing noise with deep learning-based method...

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals.

Human activity recognition and neural activity analysis are the basis for human computational neureo...

Femtosecond laser programmed artificial musculoskeletal systems.

Natural musculoskeletal systems have been widely recognized as an advanced robotic model for designi...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

The CONSORT 2010 statement provides minimum guidelines for reporting randomised trials. Its widespre...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension.

The CONSORT 2010 (Consolidated Standards of Reporting Trials) statement provides minimum guidelines ...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension.

The SPIRIT 2013 (The Standard Protocol Items: Recommendations for Interventional Trials) statement a...

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension.

The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol reporting by p...

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.

The CONSORT 2010 statement provides minimum guidelines for reporting randomized trials. Its widespre...

Molecular barcoding of native RNAs using nanopore sequencing and deep learning.

Nanopore sequencing enables direct measurement of RNA molecules without conversion to cDNA, thus ope...

PCR-detectable DNA exists a short period in the blood of systemic candidiasis murine model.

Invasive candidiasis is a major challenge to clinical medicine today. However, traditional fungal di...

Dynamic event-based state estimation for delayed artificial neural networks with multiplicative noises: A gain-scheduled approach.

This study is concerned with the state estimation issue for a kind of delayed artificial neural netw...

Pilot Study of Robot-Assisted Teleultrasound Based on 5G Network: A New Feasible Strategy for Early Imaging Assessment During COVID-19 Pandemic.

Early diagnosis is critical for the prevention and control of the coronavirus disease 2019 (COVID-19...

Objective assessment of stored blood quality by deep learning.

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo contin...

H and l-l state estimation for delayed memristive neural networks on finite horizon: The Round-Robin protocol.

In this paper, a protocol-based finite-horizon H and l-l estimation approach is put forward to solve...

Educational Value of YouTube Surgical Videos of Pediatric Robot-Assisted Laparoscopic Pyeloplasty: A Qualitative Assessment.

Surgeons and residents report using videos to prepare for procedures, with a preference for open ac...

A deep learning-based method for improving reliability of multicenter diffusion kurtosis imaging with varied acquisition protocols.

Multicenter magnetic resonance imaging is gaining more popularity in large-sample projects. Since bo...

Deep learning protocol for improved photoacoustic brain imaging.

One of the key limitations for the clinical translation of photoacoustic imaging is penetration dept...

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