AIMC Topic: Female

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A machine-learning framework for automatic reference-free quality assessment in MRI.

Magnetic resonance imaging
Magnetic resonance (MR) imaging offers a wide variety of imaging techniques. A large amount of data is created per examination which needs to be checked for sufficient quality in order to derive a meaningful diagnosis. This is a manual process and th...

A Prediction Model Using Machine Learning Algorithm for Assessing Stone-Free Status after Single Session Shock Wave Lithotripsy to Treat Ureteral Stones.

The Journal of urology
PURPOSE: The aim of this study was to develop and validate a decision support model using a machine learning algorithm to predict treatment success after single session shock wave lithotripsy in ureteral stone cases.

Postoperative bleeding risk prediction for patients undergoing colorectal surgery.

Surgery
BACKGROUND: There is limited consensus regarding risk factors for postoperative bleeding. The objective of this work was to investigate the capability of machine learning techniques in combination with practice-based longitudinal electronic medical r...

Delta activity encodes taste information in the human brain.

NeuroImage
The categorization of food via sensing nutrients or toxins is crucial to the survival of any organism. On ingestion, rapid responses within the gustatory system are required to identify the oral stimulus to guide immediate behavior (swallowing or exp...

On differentiation between vasogenic edema and non-enhancing tumor in high-grade glioma patients using a support vector machine classifier based upon pre and post-surgery MRI images.

European journal of radiology
PURPOSE: High grade gliomas (HGGs) are infiltrative in nature. Differentiation between vasogenic edema and non-contrast enhancing tumor is difficult as both appear hyperintense in T-W/FLAIR images. Most studies involving differentiation between vasog...

A Vision-Driven Collaborative Robotic Grasping System Tele-Operated by Surface Electromyography.

Sensors (Basel, Switzerland)
This paper presents a system that combines computer vision and surface electromyography techniques to perform grasping tasks with a robotic hand. In order to achieve a reliable grasping action, the vision-driven system is used to compute pre-grasping...

Improving well-being in patients with major neurodegenerative disorders: differential efficacy of brief social robot-based intervention for 3 neuropsychiatric profiles.

Clinical interventions in aging
BACKGROUND: Behavioral and psychological symptoms of dementia (BPSD) affect patients' daily life and subjective well-being. International recommendations stress nonpharmacological interventions as first-line treatment. While newer psychosocial initia...

Predicting hospital admission at emergency department triage using machine learning.

PloS one
OBJECTIVE: To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.

Diagnostic model for attention-deficit hyperactivity disorder based on interregional morphological connectivity.

Neuroscience letters
Previous brain morphology-related diagnostic models for attention-deficit hyperactivity disorder (ADHD) were based on regional features. However, building a model of individual interregional morphological connectivity is a challenging task. This stud...

Estimating risk of severe neonatal morbidity in preterm births under 32 weeks of gestation.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
A large recent study analyzed the relationship between multiple factors and neonatal outcome and in preterm births. Study variables included the reason for admission, indication for delivery, optimal steroid use, gestational age, and other potential...