AIMC Topic: Breast Neoplasms

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GPT-4o and Specialized AI in Breast Ultrasound Imaging: A Comparative Study on Accuracy, Agreement, Limitations, and Diagnostic Potential.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: This study aimed to evaluate the ability of ChatGPT and Breast Ultrasound Helper, a special ChatGPT-based subprogram trained on ultrasound image analysis, to analyze and differentiate benign and malignant breast lesions on ultrasound imag...

Exploring the potential of AI-powered applications for clinical decision-making in gynecologic oncology.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: The rise of artificial intelligence (AI) and large language models like Llama, Gemini, or Generative Pretraining Transformer (GPT) signals a promising new era in natural language processing and has significant potential for application in ...

The Role of Large Language Models (LLMs) in Breast Imaging Today and in the Near Future.

Journal of magnetic resonance imaging : JMRI
This narrative review focuses on the integration of large language models (LLMs), such as GPT-4 and Gemini, into breast imaging. LLMs excel in understanding, processing, and generating human-like text, with potential applications ranging widely from ...

Artificial Intelligence for Assessment of Digital Mammography Positioning Reveals Persistent Challenges.

Journal of breast imaging
OBJECTIVE: Mammographic breast cancer detection depends on high-quality positioning, which is traditionally assessed and monitored subjectively. This study used artificial intelligence (AI) to evaluate mammography positioning on digital screening mam...

Subtyping-Directed Precision Treatment Refines Traditional One-Size-Fits-All Therapy for HR+/HER2- Breast Cancer.

Cancer research
UNLABELLED: The standard approach of using one-size-fits-all endocrine therapy for hormone receptor (HR)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancers has faced significant challenges because of variations in tr...

AAnet Resolves a Continuum of Spatially Localized Cell States to Unveil Intratumoral Heterogeneity.

Cancer discovery
UNLABELLED: Identifying functionally important cell states and structure within heterogeneous tumors remains a significant biological and computational challenge. Current clustering- or trajectory-based models are ill-equipped to address the notion t...

Classifying the AMi-Br Mitotic Figure Dataset with AUCMEDI.

Studies in health technology and informatics
INTRODUCTION: Mitotic figure (MF) density has been established as a key biomarker for certain tumors. Recently, the differentiation between atypical MFs (AMF) and normal MFs (NMFs) has gained increased interest in research, as AMFs density could be a...

Bias in Artificial Intelligence: Impact on Breast Imaging.

Journal of breast imaging
Artificial intelligence (AI) in breast imaging has garnered significant attention given the numerous reports of improved efficiency, accuracy, and the potential to bridge the gap of expanded volume in the face of limited physician resources. While AI...

Development of a Machine Learning Model Integrating Pathomics and Clinical Data to Predict Axillary Lymph Node Metastasis in Breast Cancer: A Two-Center Study.

Cancer reports (Hoboken, N.J.)
BACKGROUND: Accurately assessing the status of axillary lymph nodes (ALNs) is essential for devising optimal surgical plans and making informed treatment decisions in breast cancer (BC) patients.

Advancements in Detection and Management of Ductal Carcinoma in Situ.

Radiographics : a review publication of the Radiological Society of North America, Inc
Ductal carcinoma in situ (DCIS) is a noninvasive breast cancer characterized by neoplastic epithelial cells confined to the ductal system by the basement membrane without invasion of adjacent tissue. Its progression to invasive carcinoma is not under...