Artificial neural network--mechanism and application in pathology

Area of Science:

• Computer Science
• Biomedical Engineering
• Pathology

Background:

• Artificial neural networks (ANNs) are computational systems inspired by the human brain's structure and function.
• ANNs hold significant potential for replicating complex cognitive processes.
• Their application in specialized fields like pathology is an emerging area of interest.

Purpose of the Study:

• To provide a concise overview of the fundamental mechanisms underlying artificial neural networks.
• To review the current and potential applications of ANNs within the field of pathology.
• To highlight the promise of ANNs in advancing pathology diagnostics and research.

Main Methods:

• This review discusses the core principles of artificial neural network architecture and function.
• It examines existing literature on ANN implementations in various pathology sub-disciplines.
• The review synthesizes information on how ANNs process data and contribute to pathological analysis.

Main Results:

• Artificial neural networks offer a unique approach to simulating human brain functions.
• ANNs have demonstrated utility in diverse areas of pathology, from image analysis to disease prediction.
• The review highlights the growing integration of ANNs in pathological workflows.

Conclusions:

• Artificial neural networks represent a powerful tool with the potential to significantly enhance higher mental functions.
• The application of ANNs in pathology is a rapidly developing field with promising implications for disease diagnosis and understanding.
• Further research and development in ANN technology are expected to drive innovation in biomedical sciences.