AIMC Topic: Female

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A generalization performance study on the boosting radiotherapy dose calculation engine based on super-resolution.

Zeitschrift fur medizinische Physik
PURPOSE: During the radiation treatment planning process, one of the time-consuming procedures is the final high-resolution dose calculation, which obstacles the wide application of the emerging online adaptive radiotherapy techniques (OLART). There ...

Effectiveness of mobile robots collecting vital signs and radiation dose rate for patients receiving Iodine-131 radiotherapy: A randomized clinical trial.

Frontiers in public health
OBJECTIVE: Patients receiving radionuclide 131I treatment expose radiation to others, and there was no clinical trial to verify the effectiveness and safety of mobile robots in radionuclide 131I isolation wards. The objective of this randomized clini...

New frontiers in embryo selection.

Journal of assisted reproduction and genetics
Human infertility is a major global public health issue estimated to affect one out of six couples, while the number of assisted reproduction cycles grows impressively year over year. Efforts to alleviate infertility using advanced technology are gai...

Deep learning of renal scans in children with antenatal hydronephrosis.

Journal of pediatric urology
INTRODUCTION: Antenatal hydronephrosis (ANH) is one of the most common anomalies identified on prenatal ultrasound, found in up to 4.5% of all pregnancies. Children with ANH are surveilled with repeated renal ultrasound and when there is high suspici...

Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment.

International journal of medical informatics
BACKGROUND: Participant recruitment is a barrier to successful clinical research. One strategy to improve recruitment is to conduct eligibility prescreening, a resource-intensive process where clinical research staff manually reviews electronic healt...

Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs.

Sensors (Basel, Switzerland)
Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in the developing fetus. Manual segmentation of fetal brain tissue is cumbersome and time-consuming, so using an automatic segmentation method can great...

Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.

PloS one
The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and progression-free survival (PFS) in breast cancer patients treated with neoa...

Tubule-U-Net: a novel dataset and deep learning-based tubule segmentation framework in whole slide images of breast cancer.

Scientific reports
The tubule index is a vital prognostic measure in breast cancer tumor grading and is visually evaluated by pathologists. In this paper, a computer-aided patch-based deep learning tubule segmentation framework, named Tubule-U-Net, is developed and pro...

Comparing State-of-the-Art Deep Learning Algorithms for the Automated Detection and Tracking of Black Cattle.

Sensors (Basel, Switzerland)
Effective livestock management is critical for cattle farms in today's competitive era of smart modern farming. To ensure farm management solutions are efficient, affordable, and scalable, the manual identification and detection of cattle are not fea...

Development of a Machine Learning Model for Sonographic Assessment of Gestational Age.

JAMA network open
IMPORTANCE: Fetal ultrasonography is essential for confirmation of gestational age (GA), and accurate GA assessment is important for providing appropriate care throughout pregnancy and for identifying complications, including fetal growth disorders. ...