AIMC Topic: Pathology

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An Introduction to Pathology Foundation Models.

Head and neck pathology
Foundation models are a recently described class of machine learning algorithms that use large amounts of data and training techniques that do not require content expert data labeling. They are trained to gain a representation of what patterns exist ...

Artificial intelligence in digital pathology diagnosis and analysis: technologies, challenges, and future prospects.

Military Medical Research
Artificial intelligence (AI) offers transformative potential in pathology, where histopathological images remain the diagnostic gold standard due to their rich morphological and molecular information. While the rapid development of AI-driven computat...

Performance of AI Chatbots on Head and Neck Pathology Board-Style Exam Questions and Guidelines for Responsible Use.

Head and neck pathology
The promising integration of artificial intelligence (AI), particularly large language models (LLMs) or AI chatbots, into medical education and practice necessitates rigorous evaluation of their capabilities. While chatbot performance has been assess...

PathoGraph: A Graph-Based Method for Standardized Representation of Pathology Knowledge.

Scientific data
Pathology data, primarily consisting of slides and diagnostic reports, inherently contain knowledge that is pivotal for advancing data-driven biomedical research and clinical practice. However, the hidden and fragmented nature of this knowledge acros...

Reshaping Organizational Culture in Pathology.

Clinics in laboratory medicine
"Reshaping Pathology Culture" explores the transformation needed in pathology departments to meet the demands of modern health care. It advocates a shift from traditional hierarchical models to collaborative leadership, uniting cross-generational pat...

Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One of the most promising areas of research that has potential clinical utility is the use of AI in patho...

Computer-assisted diagnosis to improve diagnostic pathology: A review.

Indian journal of pathology & microbiology
With an increasing demand for accuracy and efficiency in diagnostic pathology, computer-assisted diagnosis (CAD) emerges as a prominent and transformative solution. This review aims to explore the practical applications, implications, strengths, and ...

Weakly supervised multi-modal contrastive learning framework for predicting the HER2 scores in breast cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Human epidermal growth factor receptor 2 (HER2) is an important biomarker for prognosis and prediction of treatment response in breast cancer (BC). HER2 scoring is typically evaluated by pathologist microscopic observation on immunohistochemistry (IH...

Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.

Future of Artificial Intelligence-Machine Learning Trends in Pathology and Medicine.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Artificial intelligence (AI) and machine learning (ML) are transforming the field of medicine. Health care organizations are now starting to establish management strategies for integrating such platforms (AI-ML toolsets) that leverage the computation...