AIMC Topic: Urinary Bladder Neoplasms

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Machine Learning and Data Analytics in Pervasive Health.

Methods of information in medicine
INTRODUCTION: This accompanying editorial provides a brief introduction to this focus theme, focused on "Machine Learning and Data Analytics in Pervasive Health".

Multiregion segmentation of bladder cancer structures in MRI with progressive dilated convolutional networks.

Medical physics
PURPOSE: Precise segmentation of bladder walls and tumor regions is an essential step toward noninvasive identification of tumor stage and grade, which is critical for treatment decision and prognosis of patients with bladder cancer (BC). However, th...

Robotic Cystectomy-Moving from Innovation to Measurable Impact.

European urology
Data from an experienced center that randomized patients to open vs robotic cystectomy for urothelial cancer demonstrated locational differences in recurrence. While the study was not powered to detect survival differences, overall, cancer-specific, ...

Detection and Recognition for Life State of Cell Cancer Using Two-Stage Cascade CNNs.

IEEE/ACM transactions on computational biology and bioinformatics
Cancer cell detection and its stages recognition of life cycle are an important step to analyze cellular dynamics in the automation of cell based-experiments. In this work, a two-stage hierarchical method is proposed to detect and recognize different...

Development of a Natural Language Processing Engine to Generate Bladder Cancer Pathology Data for Health Services Research.

Urology
OBJECTIVE: To take the first step toward assembling population-based cohorts of patients with bladder cancer with longitudinal pathology data, we developed and validated a natural language processing (NLP) engine that abstracts pathology data from fu...

Urinary bladder cancer staging in CT urography using machine learning.

Medical physics
PURPOSE: To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).