AIMC Topic: Humans

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Time-Lapse Systems: A Comprehensive Analysis on Effectiveness.

Seminars in reproductive medicine
Time-lapse systems have quickly become a common feature of in vitro fertilization laboratories all over the world. Since being introduced over a decade ago, the alleged benefits of time-lapse technology have continued to grow, from undisturbed cultur...

Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic Kidney Disease.

Frontiers in immunology
BACKGROUND: Lipid metabolism disorder, as one major complication in patients with chronic kidney disease (CKD), is tied to an increased risk for cardiovascular disease (CVD). Traditional lipid-lowering statins have been found to have limited benefit ...

Deep learning applied to breast imaging classification and segmentation with human expert intervention.

Journal of ultrasound
PURPOSE: Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients.

Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning approach to estimate the local capillary-level input function (CIF) for pharmacokinetic model analysis of DCE-MRI.

Simultaneous robotic partial nephrectomy for bilateral renal masses.

World journal of urology
PURPOSE: There is currently no consensus regarding the optimal treatment strategy for patients presenting with synchronous bilateral renal masses. The decision to perform bilateral procedures on the same intervention or in staged procedures is debate...

Evaluation of shape factor impact on discharge coefficient of side orifices using boost simulation model with extreme learning machine data-driven.

Network (Bristol, England)
In this paper, for the first time, the impact of the shape factor on the discharge coefficient of side orifices is evaluated using the novel Extreme Learning Machine (ELM) model. In addition, the Monte Carlo simulations (MCs) are applied to assess th...

Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography.

Cardiovascular engineering and technology
PURPOSE: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for both the planning of endovascular treatment and the monitoring of the intervention's outcome, it is still performed manually implying time consuming ope...

Constraint of musculoskeletal tissue and path planning of robot-assisted fracture reduction with collision avoidance.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: For the robot-assisted fracture reduction, due to the complex fracture musculoskeletal environment, it is necessary to consider the influence of soft tissue traction on preoperative reduction path planning.

Application of deep learning algorithm on whole genome sequencing data uncovers structural variants associated with multiple mental disorders in African American patients.

Molecular psychiatry
Mental disorders present a global health concern, while the diagnosis of mental disorders can be challenging. The diagnosis is even harder for patients who have more than one type of mental disorder, especially for young toddlers who are not able to ...