BACKGROUND: Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostai...
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep n...
The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. He...
BACKGROUND: Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the ...
OBJECTIVES: To realize the automated bone age assessment by applying deep learning to digital radiography （DR） image recognition of left wrist joint in Uyghur teenagers, and explore its practical application value in forensic medicine bone age assess...
OBJECTIVES: Anterior communicating artery (ACOM) aneurysms are the most common intracranial aneurysms, and predicting their rupture risk is challenging. We aimed to predict this risk using a two-layer feed-forward artificial neural network (ANN).
Patients with type 2 diabetes mellitus are generally under continuous long-term medical treatment based on anti-diabetic drugs to achieve the desired glucose level. Thus, each patient is associated with a sequence of multiple records for prescription...
International journal of computer assisted radiology and surgery
Feb 23, 2018
OBJECTIVE: To distinguish benign from malignant pulmonary nodules using CT images is critical for their precise diagnosis and treatment. A new Agile convolutional neural network (CNN) framework is proposed to conquer the challenges of a small-scale m...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2018
Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further im...
International journal of neural systems
Feb 22, 2018
Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding ...
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