AIMC Topic: Humans

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Multi-Person Pose Estimation Using an Orientation and Occlusion Aware Deep Learning Network.

Sensors (Basel, Switzerland)
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose esti...

Automatic Detection of Arrhythmia Based on Multi-Resolution Representation of ECG Signal.

Sensors (Basel, Switzerland)
Automatic detection of arrhythmia is of great significance for early prevention and diagnosis of cardiovascular disease. Traditional feature engineering methods based on expert knowledge lack multidimensional and multi-view information abstraction an...

Stroke Prediction with Machine Learning Methods among Older Chinese.

International journal of environmental research and public health
Timely stroke diagnosis and intervention are necessary considering its high prevalence. Previous studies have mainly focused on stroke prediction with balanced data. Thus, this study aimed to develop machine learning models for predicting stroke with...

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study.

BMC musculoskeletal disorders
BACKGROUND: MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). However, there is currently no consensus as to how best to classify MRI findings which has hampered the development of robust longitudinal epidemiolog...

Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives.

AJNR. American journal of neuroradiology
Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions....

Estimating an individual's oxygen uptake during cycling exercise with a recurrent neural network trained from easy-to-obtain inputs: A pilot study.

PloS one
Measurement of oxygen uptake during exercise ([Formula: see text]) is currently non-accessible to most individuals without expensive and invasive equipment. The goal of this pilot study was to estimate cycling [Formula: see text] from easy-to-obtain ...

Introducing Hann windows for reducing edge-effects in patch-based image segmentation.

PloS one
There is a limitation in the size of an image that can be processed using computationally demanding methods such as e.g. Convolutional Neural Networks (CNNs). Furthermore, many networks are designed to work with a pre-determined fixed image size. Som...

Inferior epigastric artery pseudoaneurysm secondary to port placement during a robot-assisted laparoscopic radical cystectomy.

Journal of ultrasound
Pseudoaneurysm occurs when the artery wall is damaged and the blood is contained by the surrounding tissues with the eventual formation of a fibrous sac communicating with the artery. We report a case of a 74-year-old man with inferior epigastric art...

Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction.

European radiology
BACKGROUND AND PURPOSE: Recent studies have highlighted the importance of isocitrate dehydrogenase (IDH) mutational status in stratifying biologically distinct subgroups of gliomas. This study aimed to evaluate whether MRI-based radiomic features cou...

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.

European radiology
OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising from percutaneous lung biopsy. We evaluated the performance of a deep learning algorithm for detection of post-biopsy pneumothorax in chest radiographs ...