AIMC Topic: Mammography

Clear Filters Showing 31 to 40 of 675 articles

Detection of breast cancer using fractional discrete sinc transform based on empirical Fourier decomposition.

Bio-medical materials and engineering
Breast cancer is the most common cause of death among women worldwide. Early detection of breast cancer is important; for saving patients' lives. Ultrasound and mammography are the most common noninvasive methods for detecting breast cancer. Computer...

Quantification of Breast Arterial Calcification in Mammograms Using a UNet-Based Deep Learning for Detecting Cardiovascular Disease.

Academic radiology
BACKGROUND: Breast arterial calcification (BAC) is increasingly recognized as a significant indicator of cardiovascular risk, necessitating improvements in detection and quantification methods through mammographic screening.

Comparative analysis of semantic-segmentation models for screen film mammograms.

Computers in biology and medicine
Accurate segmentation of mammographic mass is very important as shape characteristics of these masses play a significant role for radiologist to diagnose benign and malignant cases. Recently, various deep learning segmentation algorithms have become ...

Clinical Application of AI in Mammography: Insights from a Prospective Study.

Academic radiology
RATIONALE AND OBJECTIVES: This prospective study evaluated the performance of AI in a diagnostic clinic setting, comparing its effectiveness with radiologists of varying experience.

Preoperative DBT-based radiomics for predicting axillary lymph node metastasis in breast cancer: a multi-center study.

BMC medical imaging
BACKGROUND: In the prognosis of breast cancer, the status of axillary lymph nodes (ALN) is critically important. While traditional axillary lymph node dissection (ALND) provides comprehensive information, it is associated with high risks. Sentinel ly...

Frozen Large-Scale Pretrained Vision-Language Models are the Effective Foundational Backbone for Multimodal Breast Cancer Prediction.

IEEE journal of biomedical and health informatics
Breast cancer is a pervasive global health concern among women. Leveraging multimodal data from enterprise patient databases-including Picture Archiving and Communication Systems (PACS) and Electronic Health Records (EHRs)-holds promise for improving...

A deep learning-based multimodal medical imaging model for breast cancer screening.

Scientific reports
In existing breast cancer prediction research, most models rely solely on a single type of imaging data, which limits their performance. To overcome this limitation, the present study explores breast cancer prediction models based on multimodal medic...

Can ChatGPT detect breast cancer on mammography?

Journal of medical screening
Some noteworthy studies have questioned the use of ChatGPT, a free artificial intelligence program that has become very popular and widespread in recent times, in different branches of medicine. In this study, the success of ChatGPT in detecting brea...

Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images.

Scientific reports
The most dangerous form of cancer is breast cancer. This disease is life-threatening because of its aggressive nature and high death rates. Therefore, early discovery increases the patient's survival. Mammography has recently been recommended as diag...

Development of a GPT-4-Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: Multiphase Study.

JMIR formative research
BACKGROUND: Standardized patients (SPs) prepare medical students for difficult conversations with patients. Despite their value, SP-based simulation training is constrained by available resources and competing clinical demands. Researchers are turnin...