AIMC Topic: Female

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Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks.

Medical & biological engineering & computing
Breast ultrasound (BUS) image classification in benign and malignant classes is often based on pre-trained convolutional neural networks (CNNs) to cope with small-sized training data. Nevertheless, BUS images are single-channel gray-level images, whe...

Robot-assisted laparoscopic pelvic floor surgery: Review.

Best practice & research. Clinical obstetrics & gynaecology
Minimally invasive surgical techniques have become more common in pelvic floor reconstructive urogynaecological surgery, specifically, robotic-assisted pelvic floor surgery. Female pelvic floor anatomy is complex, and some repairs require highly expe...

Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers.

Medical physics
BACKGROUND: In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated.

Effect of exoskeleton robot-assisted training on gait function in chronic stroke survivors: a systematic review of randomised controlled trials.

BMJ open
OBJECTIVES: Numbers of research have reported the usage of robot-assisted gait training for walking restoration post-stroke. However, no consistent conclusion has been reached yet about the efficacy of exoskeleton robot-assisted training (ERAT) on ga...

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.

PloS one
OBJECTIVES: The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predictive for pathological complete response pCR after Neoadjuvant chemotherapy (NAC) in locally advanced breast cancer (LABC).

The Fidelity of Artificial Intelligence to Multidisciplinary Tumor Board Recommendations for Patients with Gastric Cancer: A Retrospective Study.

Journal of gastrointestinal cancer
PURPOSE: Due to significant growth in the volume of information produced by cancer research, staying abreast of recent developments has become a challenging task. Artificial intelligence (AI) can learn, reason, and understand the enormous corpus of l...

Artificial Intelligence for Assessment of Endotracheal Tube Position on Chest Radiographs: Validation in Patients From Two Institutions.

AJR. American journal of roentgenology
Timely and accurate interpretation of chest radiographs obtained to evaluate endotracheal tube (ETT) position is important for facilitating prompt adjustment if needed. The purpose of our study was to evaluate the performance of a deep learning (DL...

The robot can break bars with the best of them: a novel approach to treating cricopharyngeal bars with myotomy.

Surgical endoscopy
INTRODUCTION: Failure of the cricopharyngeus to relax results in oropharyngeal dysphagia, which over time results in hypertrophy and increased risk for aspiration. Open myotomy is one definitive treatment option, however there are several drawbacks a...

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity.

Scientific reports
Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 p...

Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers.

European radiology experimental
High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed molecular studies have revealed marked intra-patient heterogeneity at the tumour microenvironment level, likely contributing to poor prognosis. Despite large quan...