AIMC Topic: Female

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EDLM: Ensemble Deep Learning Model to Detect Mutation for the Early Detection of Cholangiocarcinoma.

Genes
The most common cause of mortality and disability globally right now is cholangiocarcinoma, one of the worst forms of cancer that may affect people. When cholangiocarcinoma develops, the DNA of the bile duct cells is altered. Cholangiocarcinoma claim...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

PloS one
Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the potential to enhance cancer screening while also providing quantitative, objective, and highly reproduci...

Tafoxiparin, a novel drug candidate for cervical ripening and labor augmentation: results from 2 randomized, placebo-controlled studies.

American journal of obstetrics and gynecology
BACKGROUND: Slow progression of labor is a common obstetrical problem with multiple associated complications. Tafoxiparin is a depolymerized form of heparin with a molecular structure that eliminates the anticoagulant effects of heparin. We report on...

Robot-assisted nipple-sparing mastectomy and immediate breast reconstruction with gel implant and latissimus dorsi muscle flap: Our initial experience.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: This study reports the preliminary results of da Vinci robot XI robot-assisted nipple-sparing mastectomy immediate breast reconstruction (R-NSMIBR) with gel implant and latissimus dorsi muscle flap.

Machine learning functional impairment classification with electronic health record data.

Journal of the American Geriatrics Society
BACKGROUND: Poor functional status is a key marker of morbidity, yet is not routinely captured in clinical encounters. We developed and evaluated the accuracy of a machine learning algorithm that leveraged electronic health record (EHR) data to provi...

Identifying ex vivo acute ischemic stroke thrombus composition using electrochemical impedance spectroscopy.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BackgroundIntra-procedural characterization of stroke thromboemboli might guide mechanical thrombectomy (MT) device choice to improve recanalization rates. Electrochemical impedance spectroscopy (EIS) has been used to characterize various biological ...

Diagnostic performance of deep learning-based reconstruction algorithm in 3D MR neurography.

Skeletal radiology
OBJECTIVE: The study aims to evaluate the diagnostic performance of deep learning-based reconstruction method (DLRecon) in 3D MR neurography for assessment of the brachial and lumbosacral plexus.

Effect of artificial intelligence-based computer-aided diagnosis on the screening outcomes of digital mammography: a matched cohort study.

European radiology
OBJECTIVE: To investigate whether artificial intelligence-based computer-aided diagnosis (AI-CAD) can improve radiologists' performance when used to support radiologists' interpretation of digital mammography (DM) in breast cancer screening.

Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study.

Journal of nursing management
BACKGROUND: Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms amon...

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death.

Biotechnology & genetic engineering reviews
This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death (SCD). 320 SCD patients who met the inclusion and exclusion criteria underwent clinical evaluation,...