Segmentation of brain lesions from magnetic resonance images (MRI) is an important step for disease diagnosis, surgical planning, radiotherapy and chemotherapy. However, due to noise, motion, and partial volume effects, automated segmentation of lesi...
International journal of urology : official journal of the Japanese Urological Association
Feb 11, 2020
OBJECTIVES: To investigate intraocular pressure and visual function in patients with ocular diseases undergoing robot-assisted laparoscopic prostatectomy.
BACKGROUND: Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('p...
Clinical pharmacology and therapeutics
Feb 11, 2020
When treating multiple complex diseases, such as cancer, polytherapy may demonstrate efficiency than monotherapy. However, due to the multiplicative relationship between the number of drugs and cell lines vs. the number of combinations, it is impract...
Head and neck squamous cell carcinoma (HNSCC) is the sixth malignancy, which is characterized by poor prognosis or high mortality because of the lack of predicting markers. Aberrant cancer pseudogenes have been found predictive for prognosis. We aim ...
Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method ...
Alzheimer's & dementia : the journal of the Alzheimer's Association
Feb 11, 2020
INTRODUCTION: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer's disease (AD) is a critical yet unmet clinical challenge.
Deep Learning (DL), a successful promising approach for discriminative and generative tasks, has recently proved its high potential in 2D medical imaging analysis; however, physiological data in the form of 1D signals have yet to be beneficially expl...
Prediction rule ensembles (PREs) are a relatively new statistical learning method, which aim to strike a balance between predictive performance and interpretability. Starting from a decision tree ensemble, like a boosted tree ensemble or a random for...
IEEE journal of biomedical and health informatics
Feb 10, 2020
Medicine has entered the digital era, driven by data from new modalities, especially genomics and imaging, as well as new sources such as wearables and Internet of Things. As we gain a deeper understanding of the disease biology and how diseases affe...
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