AIMC Topic: Breast Neoplasms

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AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models.

Journal of the American Medical Informatics Association : JAMIA Jan 18, 2024
OBJECTIVES: We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the ...
Female Breast Neoplasms Natural Language Processing Information Storage and Retrieval Eligibility Determination Humans Language
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Comparative Analysis of Data Generation Techniques for Breast Cancer Research Using Artificial Intelligence.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
This study investigates the use of ChatGPT to support clinical teams with limited expertise in generating synthetic data for breast cancer research. It assesses ChatGPT's application, focusing on effective prompting and best practices for creating hi...
Humans Artificial Intelligence Machine Learning Biomedical Research Female Breast Neoplasms
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Exposing Vulnerabilities in Clinical LLMs Through Data Poisoning Attacks: Case Study in Breast Cancer.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
Training Large Language Models (LLMs) with billions of parameters on a dataset and publishing the model for public access is the current standard practice. Despite their transformative impact on natural language processing (NLP), public LLMs present ...
Breast Neoplasms Humans Natural Language Processing Female Computer Security
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A Multi-Task Learning Approach for Segmentation of Breast Arterial Calcifications in Screening Mammograms.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
Screening mammogram is a standard and cost-efficient imaging procedure to measure breast cancer risk among 45+ year old women. Quantifying breast arterial calcification (BAC) from screening mammograms is a non-invasive and cost-efficient approach to ...
Radiographic Image Interpretation, Computer-Assisted Breast Vascular Calcification Breast Neoplasms Middle Aged Mammography Humans Machine Learning Female
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Integrating AI into Clinical Workflows: A Simulation Study on Implementing AI-aided Same-day Diagnostic Testing Following an Abnormal Screening Mammogram.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
Artificial intelligence (AI) shows promise in clinical tasks, yet its integration into workflows remains underexplored. This study proposes an AI-aided same-day diagnostic imaging workup to reduce recall rates following abnormal screening mammograms ...
Female Breast Neoplasms Mammography Workflow Humans Artificial Intelligence Computer Simulation
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A Multi-label Artificial Intelligence Approach for Improving Breast Cancer Detection With Mammographic Image Analysis.

In vivo (Athens, Greece) Jan 1, 2024
BACKGROUND/AIM: Breast cancer remains a major global health concern. This study aimed to develop a deep-learning-based artificial intelligence (AI) model that predicts the malignancy of mammographic lesions and reduces unnecessary biopsies in patient...
Retrospective Studies Female Breast Neoplasms Humans Artificial Intelligence Algorithms Radiographic Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Mammography
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Radiomic Machine Learning in Invasive Ductal Breast Cancer: Prediction of Ki-67 Expression Level Based on Radiomics of DCE-MRI.

Technology in cancer research & treatment Jan 1, 2024
PURPOSE: Our study aimed to investigate the potential of radiomics with DCE-MRI for predicting Ki-67 expression in invasive ductal breast cancer.
Carcinoma, Ductal, Breast Adult Magnetic Resonance Imaging Ki-67 Antigen Breast Neoplasms Area Under Curve Biomarkers, Tumor Retrospective Studies Humans Image Interpretation, Computer-Assisted Radiomics Middle Aged Female Machine Learning ROC Curve Aged Prognosis
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Parametric optimization and comparative study of machine learning and deep learning algorithms for breast cancer diagnosis.

Breast disease Jan 1, 2024
Breast Cancer is the leading form of cancer found in women and a major cause of increased mortality rates among them. However, manual diagnosis of the disease is time-consuming and often limited by the availability of screening systems. Thus, there i...
Data Mining Humans Breast Neoplasms Machine Learning Diagnosis, Computer-Assisted Algorithms Deep Learning Female
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Insights into a Machine Learning-Based Palmitoylation-Related Gene Model for Predicting the Prognosis and Treatment Response of Breast Cancer Patients.

Technology in cancer research & treatment Jan 1, 2024
BACKGROUND: Breast cancer is a prevalent public health concern affecting numerous women globally and is associated with palmitoylation, a post-translational protein modification. Despite increasing focus on palmitoylation, its specific implications f...
Biomarkers, Tumor Gene Expression Profiling Transcriptome Gene Regulatory Networks Computational Biology Immunotherapy Prognosis Female Breast Neoplasms Lipoylation Humans Gene Expression Regulation, Neoplastic Machine Learning Nomograms Treatment Outcome
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'Humans think outside the pixels' - Radiologists' perceptions of using artificial intelligence for breast cancer detection in mammography screening in a clinical setting.

Health informatics journal Jan 1, 2024
OBJECTIVE: This study aimed to explore radiologists' views on using an artificial intelligence (AI) tool named ScreenTrustCAD with Philips equipment) as a diagnostic decision support tool in mammography screening during a clinical trial at Capio Sank...
Qualitative Research Interviews as Topic Early Detection of Cancer Mammography Radiologists Perception Adult Humans Breast Neoplasms Middle Aged Artificial Intelligence Female Sweden
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