AIMC Topic: Female

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Deep fit_predic: a novel integrated pyramid dilation EfficientNet-B3 scheme for fitness prediction system.

Computer methods in biomechanics and biomedical engineering
This study introduces novel deep learning (DL) techniques for effective fitness prediction using a person's health data. Initially, pre-processing is performed in which data cleaning, one-hot encoding and data normalization are performed. The pre-pro...

Multidirectional Traction Method Using SURGICEL NU-KNIT and Surgical Suture in Robot-assisted Laparoscopic Surgery for Endometrial Cancer.

Journal of minimally invasive gynecology
OBJECTIVE: To describe a novel approach to robot-assisted laparoscopic total hysterectomy (RH) for endometrial cancer that minimizes cancer sell spillage and develops a stable surgical field.

Machine learning based assessment of preclinical health questionnaires.

International journal of medical informatics
BACKGROUND: Within modern health systems, the possibility of accessing a large amount and a variety of data related to patients' health has increased significantly over the years. The source of this data could be mobile and wearable electronic system...

Surgical skill level classification model development using EEG and eye-gaze data and machine learning algorithms.

Journal of robotic surgery
The aim of this study was to develop machine learning classification models using electroencephalogram (EEG) and eye-gaze features to predict the level of surgical expertise in robot-assisted surgery (RAS). EEG and eye-gaze data were recorded from 11...

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning.

Surgery today
PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

European radiology
OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model.

Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers.

Scientific reports
Ultrasound imaging is commonly used to aid in fetal development. It has the advantage of being real-time, low-cost, non-invasive, and easy to use. However, fetal organ detection is a challenging task for obstetricians, it depends on several factors, ...

Accelerated Cine Cardiac MRI Using Deep Learning-Based Reconstruction: A Systematic Evaluation.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Breath-holding (BH) for cine balanced steady state free precession (bSSFP) imaging is challenging for patients with impaired BH capacity. Deep learning-based reconstruction (DLR) of undersampled k-space promises to shorten BHs while prese...