AIMC Topic: Female

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Ranking attention multiple instance learning for lymph node metastasis prediction on multicenter cervical cancer MRI.

Journal of applied clinical medical physics
PURPOSE: In the current clinical diagnostic process, the gold standard for lymph node metastasis (LNM) diagnosis is histopathological examination following surgical lymphadenectomy. Developing a non-invasive and preoperative method for predicting LNM...

Prediction of pathological complete response to chemotherapy for breast cancer using deep neural network with uncertainty quantification.

Medical physics
BACKGROUND: The I-SPY 2 trial is a national-wide, multi-institutional clinical trial designed to evaluate multiple new therapeutic drugs for high-risk breast cancer. Previous studies suggest that pathological complete response (pCR) is a viable indic...

A new scoring in differential diagnosis: multisystem inflammatory syndrome or adenovirus infection?

Turkish journal of medical sciences
BACKGROUND/AIM: Differentiating multisystem inflammatory syndrome in children (MIS-C) from adenovirus infection (AI) can be challenging due to similar clinical and laboratory findings. This study aimed to identify distinguishing characteristics and d...

Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration.

Journal of advanced research
INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment.

Interpretable machine learning model for predicting the prognosis of antibody positive autoimmune encephalitis patients.

Journal of affective disorders
OBJECTIVE: The objective was to utilize nine machine learning (ML) methods to predict the prognosis of antibody positive autoimmune encephalitis (AE) patients.

MG-Net: A fetal brain tissue segmentation method based on multiscale feature fusion and graph convolution attention mechanisms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fetal brain tissue segmentation provides foundational support for comprehensively understanding the neurodevelopment of normal and congenital disease-affected fetuses. Manual labeling is very time-consuming, and automated se...