Data classification is one of the most commonly used applications of machine learning. The are many developed algorithms that can work in various environments and for different data distributions that perform this task with excellence. Classification...
OBJECTIVES: To develop a classification system for urine cytology with artificial intelligence (AI) using a convolutional neural network algorithm that classifies urine cell images as negative (benign) or positive (atypical or malignant).
PURPOSE: In this paper, we utilized deep learning methods to screen the positive COVID-19 cases in chest CT. Our primary goal is to supply rapid and precise assistance for disease surveillance on the medical imaging aspect.
Interdisciplinary sciences, computational life sciences
Jul 5, 2021
The disease Alzheimer is an irrepressible neurologicalbrain disorder. Earlier detection and proper treatment of Alzheimer's disease can help for brain tissue damage prevention. The study was intended to explore the segmentation effects of convolution...
OBJECTIVES: We retrospectively investigated if robot-assisted laparoscopic partial nephrectomy (RAPN) contributes to a decrease in resected parenchymal volume (RPV), an increase in postoperative parenchymal volume (PPV), and an improvement of postope...
Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support...
The international journal of medical robotics + computer assisted surgery : MRCAS
Jul 5, 2021
BACKGROUND: This paper describes a case of a patient with situs inversus totalis (SIT) and dextrocardia in which robotic atrial septal defect (ASD) repair was successfully performed in a beating heart.
3D printing (3DP) is a progressive technology capable of transforming pharmaceutical development. However, despite its promising advantages, its transition into clinical settings remains slow. To make the vital leap to mainstream clinical practice an...
OBJECTIVES: To develop a model for predicting biochemical recurrence (BCR) in patients with long follow-up periods using clinical parameters and the machine learning (ML) methods.
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