AI Medical Compendium Topic

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Validation Studies as Topic

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Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study.

JMIR mHealth and uHealth
BACKGROUND: Wearable accelerometers have greatly improved measurement of physical activity, and the increasing popularity of smartwatches with inherent acceleration data collection suggest their potential use in the physical activity research domain;...

Automated Closed- and Open-Loop Validation of Knowledge-Based Planning Routines Across Multiple Disease Sites.

Practical radiation oncology
PURPOSE: Knowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority o...

Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we de...

The Deep Learning-Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: It is of great importance for researchers to publish research results in high-quality journals. However, it is often challenging to choose the most suitable publication venue, given the exponential growth of journals and conferences. Alth...

Applying density-based outlier identifications using multiple datasets for validation of stroke clinical outcomes.

International journal of medical informatics
INTRODUCTION: Clinicians commonly use the modified Rankin Scale (mRS) and the Barthel Index (BI) to measure clinical outcome after stroke. These are potential targets in machine learning models for stroke outcome prediction. Therefore, the quality of...

Filtering maxRatio results with machine learning models increases quantitative PCR accuracy over the fit point method.

Journal of microbiological methods
With qPCR reaching thousands of reactions per run, assay validation needs automation. We applied support vector machine to qPCR analysis and we could identify reactions with 100% accuracy, dispensing them from further validation. We achieved a greatl...

Features spaces and a learning system for structural-temporal data, and their application on a use case of real-time communication network validation data.

PloS one
The service quality and system dependability of real-time communication networks strongly depends on the analysis of monitored data, to identify concrete problems and their causes. Many of these can be described by either their structural or temporal...

Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations.

European radiology
Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be practiced in the near future, but several issues need to be resolved before AI can be widely implemented in daily practice. These include the role of th...

Virtual reality operating room with AI guidance: design and validation of a fire scenario.

Surgical endoscopy
BACKGROUND: Operating room (OR) fires are uncommon but disastrous events. Inappropriate handling of OR fires can result in injuries, even death. Aiming to simulate OR fire emergencies and effectively train clinicians to react appropriately, we have d...

Learning Latent Space Representations to Predict Patient Outcomes: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Scalable and accurate health outcome prediction using electronic health record (EHR) data has gained much attention in research recently. Previous machine learning models mostly ignore relations between different types of clinical data (i...