AIMC Topic: Humans

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Deep learning-accelerated T2-weighted imaging of the prostate: Impact of further acceleration with lower spatial resolution on image quality.

European journal of radiology
PURPOSE: To compare image quality in prostate MRI among standard T2-weighted imaging (T2-std), accelerated T2-weighted imaging (T2WI) with high resolution (T2-HR) and more accelerated T2WI with lower resolution (T2-LR) using both conventional reconst...

Imputation of sensory properties using deep learning.

Journal of computer-aided molecular design
Predicting the sensory properties of compounds is challenging due to the subjective nature of the experimental measurements. This testing relies on a panel of human participants and is therefore also expensive and time-consuming. We describe the appl...

Heterogeneous treatment effect analysis based on machine-learning methodology.

CPT: pharmacometrics & systems pharmacology
Heterogeneous treatment effect (HTE) analysis focuses on examining varying treatment effects for individuals or subgroups in a population. For example, an HTE-informed understanding can critically guide physicians to individualize the medical treatme...

A CSI-Based Human Activity Recognition Using Deep Learning.

Sensors (Basel, Switzerland)
The Internet of Things (IoT) has become quite popular due to advancements in Information and Communications technologies and has revolutionized the entire research area in Human Activity Recognition (HAR). For the HAR task, vision-based and sensor-ba...

srBERT: automatic article classification model for systematic review using BERT.

Systematic reviews
BACKGROUND: Systematic reviews (SRs) are recognized as reliable evidence, which enables evidence-based medicine to be applied to clinical practice. However, owing to the significant efforts required for an SR, its creation is time-consuming, which of...

Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.

Journal of electrocardiology
BACKGROUND: Patients with chest pain and persistent ST segment elevation (STE) may not have acute coronary occlusions or serum troponin curves suggestive of acute necrosis. Our objective is the validation and cost-effectiveness analysis of a diagnost...

Neural Network-Oriented Big Data Model for Yoga Movement Recognition.

Computational intelligence and neuroscience
The use of computer vision for target detection and recognition has been an interesting and challenging area of research for the past three decades. Professional athletes and sports enthusiasts in general can be trained with appropriate systems for c...

Machine learning to guide clinical decision-making in abdominal surgery-a systematic literature review.

Langenbeck's archives of surgery
PURPOSE: An indication for surgical therapy includes balancing benefits against risk, which remains a key task in all surgical disciplines. Decisions are oftentimes based on clinical experience while guidelines lack evidence-based background. Various...

What will we ask to artificial intelligence for cardiovascular medicine in the next decade?

Minerva cardiology and angiology
Artificial intelligence (AI) comprises a wide range of technologies and methods with heterogeneous degrees of complexity, applications, and abilities. In the cardiovascular field, AI holds the potential to fulfil many unsolved challenges, eventually ...