AIMC Topic: Humans

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Machine learning-based approach reveals essential features for simplified TSPO PET quantification in ischemic stroke patients.

Zeitschrift fur medizinische Physik
INTRODUCTION: Neuroinflammation evaluation after acute ischemic stroke is a promising option for selecting an appropriate post-stroke treatment strategy. To assess neuroinflammation in vivo, translocator protein PET (TSPO PET) can be used. However, t...

Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes.

Psychotherapy research : journal of the Society for Psychotherapy Research
The occurrence of dropout from psychological interventions is associated with poor treatment outcome and high health, societal and economic costs. Recently, machine learning (ML) algorithms have been tested in psychotherapy outcome research. Dropout...

Real-time fundus reconstruction and intraocular mapping using an ophthalmic endoscope.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robotic ophthalmic endoscope holders allow surgeons to execute dual-hand operations in eye surgery. To prevent needle-like endoscopes from invading the retina when moving, surgeons expect visual and real-time information about the relativ...

The Surgical Learning Curve: Does Robotic Technical Skill Explain Differences in Operative Performance?

Journal of laparoendoscopic & advanced surgical techniques. Part A
Prior studies on technical skills use small collections of videos for assessment. However, there is likely heterogeneity of performance among surgeons and likely improvement after training. If technical skill explains these differences, then it shou...

Extensive deep learning model to enhance electrocardiogram application via latent cardiovascular feature extraction from identity identification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Deep learning models (DLMs) have been successfully applied in biomedicine primarily using supervised learning with large, annotated databases. However, scarce training resources limit the potential of DLMs for electrocardiog...

FUN-SIS: A Fully UNsupervised approach for Surgical Instrument Segmentation.

Medical image analysis
Automatic surgical instrument segmentation of endoscopic images is a crucial building block of many computer-assistance applications for minimally invasive surgery. So far, state-of-the-art approaches completely rely on the availability of a ground-t...

XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department.

Artificial intelligence in medicine
Nowadays it is increasingly important in many applications to understand how different factors influence a variable of interest in a predictive modeling process. This task becomes particularly important in the context of Explainable Artificial Intell...