AIMC Topic: Female

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A deep learning framework to classify breast density with noisy labels regularization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast density assessed from digital mammograms is a biomarker for higher risk of developing breast cancer. Experienced radiologists assess breast density using the Breast Image and Data System (BI-RADS) categories. Supervis...

Automated medical chart review for breast cancer outcomes research: a novel natural language processing extraction system.

BMC medical research methodology
BACKGROUND: Manually extracted data points from health records are collated on an institutional, provincial, and national level to facilitate clinical research. However, the labour-intensive clinical chart review process puts an increasing burden on ...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

Archives of gynecology and obstetrics
In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric decision-making algorithms. Regarding ovarian cancer (OC), despite the standardization of features t...

RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model.

Sensors (Basel, Switzerland)
Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to propose an image processing algorithm based on acetowhite, which is an important criterion for diag...

Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning.

Skeletal radiology
OBJECTIVE: We aimed to perform an external validation of an existing commercial AI software program (BoneView™) for the detection of acute appendicular fractures in pediatric patients.

Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.

BMC musculoskeletal disorders
BACKGROUND: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This stu...

The effect of robotic rehabilitation on posture and trunk control in non-ambulatory cerebral palsy.

Assistive technology : the official journal of RESNA
The purpose of this study was to investigate the effects of a combined robot-assisted gait training (RAGT) with standard physiotherapy (PT) on trunk control and posture in non-ambulatory children with cerebral palsy (CP). This nonrandomized, controll...

Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review.

Computers in biology and medicine
Being a second most cause of mortality worldwide, cancer has been identified as a perilous disease for human beings, where advance stage diagnosis may not help much in safeguarding patients from mortality. Thus, efforts to provide a sustainable archi...

Fluorescence Analysis of Circulating Exosomes for Breast Cancer Diagnosis Using a Sensor Array and Deep Learning.

ACS sensors
Emerging liquid biopsy methods for investigating biomarkers in bodily fluids such as blood, saliva, or urine can be used to perform noninvasive cancer detection. However, the complexity and heterogeneity of exosomes require improved methods to achiev...

Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix.

PloS one
Breast cancer is regarded as the leading killer of women today. The early diagnosis and treatment of breast cancer is the key to improving the survival rate of patients. A method of breast cancer histopathological images recognition based on deep sem...