AIMC Topic: Machine Learning

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Using Machine Learning to Identify Intravenous Contrast Phases on Computed Tomography.

Computer methods and programs in biomedicine
PURPOSE: The purpose of the present work is to demonstrate the application of machine learning (ML) techniques to automatically identify the presence and physiologic phase of intravenous (IV) contrast in Computed Tomography (CT) scans of the Chest, A...

A multi-stage machine learning model for diagnosis of esophageal manometry.

Artificial intelligence in medicine
High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its manual interpretation and classification, including evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based...

Design of a rapid diagnostic model for bladder compliance based on real-time intravesical pressure monitoring system.

Computers in biology and medicine
OBJECTIVE: The diagnosis of bladder dysfunction for children depends on the confirmation of abnormal bladder shape and bladder compliance. The existing gold standard needs to conduct voiding cystourethrogram (VCUG) examination and urodynamic studies ...

Use of machine learning to classify high-risk variants of uncertain significance in lamin A/C cardiac disease.

Heart rhythm
BACKGROUND: Variation in lamin A/C results in a spectrum of clinical disease, including arrhythmias and cardiomyopathy. Benign variation is rare, and classification of LMNA missense variants via in silico prediction tools results in a high rate of va...

Deep learning models for image and data processes of intracellular calcium ions.

Cellular signalling
Intracellular calcium ion (Ca) in cytoplasm as an intracellular second messenger is involved in almost all important cellular activities of organisms. Generally its concentration ([Ca]) is tested by live imaging followed image and data processes, in ...

Domain generalization on medical imaging classification using episodic training with task augmentation.

Computers in biology and medicine
Medical imaging datasets usually exhibit domain shift due to the variations of scanner vendors, imaging protocols, etc. This raises the concern about the generalization capacity of machine learning models. Domain generalization (DG), which aims to le...

Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Circulation. Heart failure
BACKGROUND: Prospective studies demonstrate that aggressive pharmacological therapy combined with pump speed optimization may result in myocardial recovery in larger numbers of patients supported with left ventricular assist device (LVAD). This study...

Human-in-the-loop Extraction of Interpretable Concepts in Deep Learning Models.

IEEE transactions on visualization and computer graphics
The interpretation of deep neural networks (DNNs) has become a key topic as more and more people apply them to solve various problems and making critical decisions. Concept-based explanations have recently become a popular approach for post-hoc inter...

Recognition of Maize Phenology in Sentinel Images with Machine Learning.

Sensors (Basel, Switzerland)
The scarcity of water for agricultural use is a serious problem that has increased due to intense droughts, poor management, and deficiencies in the distribution and application of the resource. The monitoring of crops through satellite image process...

Development of a prediction score for in-hospital mortality in COVID-19 patients with acute kidney injury: a machine learning approach.

Scientific reports
Acute kidney injury (AKI) is frequently associated with COVID-19 and it is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting in-hospital mortality in COVID-19 patients with AKI (AKI-COV score)....