AI Medical Compendium Topic

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Chronic Disease

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Machine learning to improve frequent emergency department use prediction: a retrospective cohort study.

Scientific reports
Frequent emergency department use is associated with many adverse events, such as increased risk for hospitalization and mortality. Frequent users have complex needs and associated factors are commonly evaluated using logistic regression. However, ot...

Intra-person multi-task learning method for chronic-disease prediction.

Scientific reports
In the medical field, various clinical information has been accumulated to help clinicians provide personalized medicine and make better diagnoses. As chronic diseases share similar characteristics, it is possible to predict multiple chronic diseases...

A multi-task convolutional neural network for classification and segmentation of chronic venous disorders.

Scientific reports
Chronic Venous Disorders (CVD) of the lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North America. Due to the exponential growth of the aging population and the worsening of CVD with age, it is ex...

Causal deep learning reveals the comparative effectiveness of antihyperglycemic treatments in poorly controlled diabetes.

Nature communications
Type-2 diabetes is associated with severe health outcomes, the effects of which are responsible for approximately 1/4 of the total healthcare spending in the United States (US). Current treatment guidelines endorse a massive number of potential anti-...

Continuum robots for endoscopic sinus surgery: Recent advances, challenges, and prospects.

The international journal of medical robotics + computer assisted surgery : MRCAS
PURPOSE: Endoscopic sinus surgery (ESS) has been recognized as an effective treatment modality for paranasal sinus diseases. Over the past decade, continuum robots (CRs) for ESS have been studied, but there are still some challenges. This paper prese...

Deep Learning Segmentation and Reconstruction for CT of Chronic Total Coronary Occlusion.

Radiology
Background CT imaging of chronic total occlusion (CTO) is useful in guiding revascularization, but manual reconstruction and quantification are time consuming. Purpose To develop and validate a deep learning (DL) model for automated CTO reconstructio...

Exploration of biomedical knowledge for recurrent glioblastoma using natural language processing deep learning models.

BMC medical informatics and decision making
BACKGROUND: Efficient exploration of knowledge for the treatment of recurrent glioblastoma (GBM) is critical for both clinicians and researchers. However, due to the large number of clinical trials and published articles, searching for this knowledge...

ConcentrateNet: Multi-Scale Object Detection Model for Advanced Driving Assistance System Using Real-Time Distant Region Locating Technique.

Sensors (Basel, Switzerland)
This paper proposes a deep learning based object detection method to locate a distant region in an image in real-time. It concentrates on distant objects from a vehicular front camcorder perspective, trying to solve one of the common problems in Adva...

A Precision Health Service for Chronic Diseases: Development and Cohort Study Using Wearable Device, Machine Learning, and Deep Learning.

IEEE journal of translational engineering in health and medicine
This paper presents an integrated and scalable precision health service for health promotion and chronic disease prevention. Continuous real-time monitoring of lifestyle and environmental factors is implemented by integrating wearable devices, open e...