AIMC Topic: Female

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Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.

European radiology
OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-c...

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates.

European radiology
OBJECTIVES: Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphom...

Unplanned conversions of robotic pancreaticoduodenectomy: short-term outcomes and suggested stepwise approach for a safe conversion.

Surgical endoscopy
OBJECTIVE: With the increased adoption of robotic pancreaticoduodenectomy, the effects of unplanned conversions to an 'open' operation are ill-defined. This study aims to describe the impact of unplanned conversions of robotic pancreaticoduodenectomy...

Employing Atrous Pyramid Convolutional Deep Learning Approach for Detection to Diagnose Breast Cancer Tumors.

Computational intelligence and neuroscience
Breast cancer is among the most common diseases and one of the most common causes of death in the female population worldwide. Early identification of breast cancer improves survival. Therefore, radiologists will be able to make more accurate diagnos...

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM ...

Performance of artificial intelligence in 7533 consecutive prevalent screening mammograms from the BreastScreen Australia program.

European radiology
OBJECTIVES: To assess the performance of an artificial intelligence (AI) algorithm in the Australian mammography screening program which routinely uses two independent readers with arbitration of discordant results.

The use of a porcine model to teach advanced abdominal wall dissection techniques.

Surgical endoscopy
BACKGROUND: In the era of minimally invasive surgery, it is clear that a robust simulation model is required for the training of surgeons in advanced abdominal wall reconstruction. The purpose of this experimentation was to evaluate whether a porcine...

Robotic and laparoscopic sphincter-saving resections have similar peri-operative, oncological and functional outcomes in female patients with rectal cancer.

Updates in surgery
BACKGROUND: This study aimed to compare perioperative, long-term oncological, and anorectal functional outcomes of robotic total mesorectal excision (R-TME) and laparoscopic total mesorectal excision (L-TME) sphincter-saving total mesorectal excision...

PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.

Breast cancer research : BCR
BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict t...

A systematic review of the development and application of home cage monitoring in laboratory mice and rats.

BMC biology
BACKGROUND: Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors an...