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Blood Pressure Estimation Using Explainable Deep-Learning Models Based on Photoplethysmography.
Anesthesia and analgesia
Dec 16, 2024
BACKGROUND: Due to their invasiveness, arterial lines are not typically used in routine monitoring, despite their superior responsiveness in hemodynamic monitoring and detecting intraoperative hypotension. To address this issue, noninvasive, continuo...
Interpretable deep learning survival predictions in sporadic Creutzfeldt-Jakob disease.
Journal of neurology
Dec 16, 2024
BACKGROUND: Sporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive and fatal prion disease with significant public health implications. Survival is heterogenous, posing challenges for prognostication and care planning. We developed a surv...
Utilizing machine learning approaches to investigate the relationship between cystatin C and serious complications in esophageal cancer patients after esophagectomy.
Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Dec 16, 2024
BACKGROUND: The purpose of this study is to investigate the relationship between preoperative cystatin C levels and the risk of serious postoperative complications in esophageal cancer (EC) patients, utilizing advanced machine learning (ML) methodolo...
Swing limb detection using a convolutional neural network and a sequential hypothesis test based on foot pressure data during gait initialization in individuals with Parkinson's disease.
Physiological measurement
Dec 16, 2024
. Start hesitation is a key issue for individuals with Parkinson's disease (PD) during gait initiation. Visual cues have proven effective in enhancing gait initiation. When applied to laser-light shoes, swing-limb detection efficiently activates the ...
Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials.
Frontiers in public health
Dec 16, 2024
INTRODUCTION: Smart cities, artificial intelligence (AI) in healthcare, and low-carbon building materials are pivotal to public health, environmental sustainability, and green efficiency. Despite their critical importance, understanding public percep...
Impaired interhemispheric synchrony in patients with iridocyclitis and classification using machine learning: an fMRI study.
Frontiers in immunology
Dec 16, 2024
BACKGROUND: This study examined the interhemispheric integration function pattern in patients with iridocyclitis utilizing the voxel-mirrored homotopic connectivity (VMHC) technique. Additionally, we investigated the ability of VMHC results to distin...
Estimation of foveal avascular zone area from a B-scan OCT image using machine learning algorithms.
PloS one
Dec 16, 2024
PURPOSE: The objective of this study is to estimate the area of the Foveal Avascular Zone (FAZ) from B-scan OCT images using machine learning algorithms.
Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Dec 14, 2024
INTRODUCTION: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.
Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method.
Magnetic resonance imaging
Dec 14, 2024
PURPOSE: To develop a multi-parametric MRI model for the prediction of molecular subtypes of breast cancer using five types of breast cancer preoperative MRI images.
Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology.
Sensors (Basel, Switzerland)
Dec 14, 2024
Wearable accelerometers are widely used as an ecologically valid and scalable solution for long-term at-home sleep monitoring in both clinical research and care. In this study, we applied a deep learning domain adversarial convolutional neural networ...
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