Hospital-Based Medicine

Risk Management

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

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Towards the adoption of quantitative computed tomography in the management of interstitial lung disease.

The shortcomings of qualitative visual assessment have led to the development of computer-based tool...

Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network.

Despite technological advances in the proteomics field, sample preparation still represents the main...

Deep Learning Model to Evaluate Sensorimotor System Ability in Patients With Dizziness for Postural Control.

Balanced posture without dizziness is achieved via harmonious coordination of visual, vestibular, an...

Artificial intelligence tools for optimising recruitment and retention in clinical trials: a scoping review protocol.

INTRODUCTION: In recent years, the influence of artificial intelligence technology on clinical trial...

[Ethics and artificial intelligence].

The introduction of artificial intelligence (AI) into radiology promises to enhance efficiency and i...

Comparative analysis of radiation exposure in robot-assisted total knee arthroplasty using popular robotic systems.

Robotic-assisted TKA (RATKA) is a rapidly emerging technique that has been shown to improve precisio...

Checklist for Reproducibility of Deep Learning in Medical Imaging.

The application of deep learning (DL) in medicine introduces transformative tools with the potential...

Facilitators and barriers to codesigning social robots with older adults with dementia: a scoping review protocol.

INTRODUCTION: Social robots including telepresence robots have emerged as potential support in demen...

Real-world artificial intelligence-based interpretation of fundus imaging as part of an eyewear prescription renewal protocol.

OBJECTIVE: A real-world evaluation of the diagnostic accuracy of the Opthai® software for artificial...

An Introductory Guide to Artificial Intelligence in Interventional Radiology: Part 2: Implementation Considerations and Harms.

The introduction of artificial intelligence (AI) in interventional radiology (IR) will bring about n...

Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.

Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identi...

Charting the future of patient care: A strategic leadership guide to harnessing the potential of artificial intelligence.

Artificial Intelligence (AI) applications have the potential to revolutionize conventional healthcar...

Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting a...

Monitoring performance of clinical artificial intelligence: a scoping review protocol.

OBJECTIVE: The objective of this scoping review is to describe the scope and nature of research on t...

Efficacy of the Addition of Robot-assisted Radical Cystectomy with Extracorporeal Urinary Diversion after an Enhanced Recovery Protocol.

PURPOSE: It is unclear if robotic radical cystectomy with extracorporeal urinary diversion (eRARC) p...

Deep-learning image analysis for high-throughput screening of opsono-phagocytosis-promoting monoclonal antibodies against Neisseria gonorrhoeae.

Antimicrobial resistance (AMR) is nowadays a global health concern as bacterial pathogens are increa...

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