Breast cancer is the leading cause of death for women worldwide. Regular breast cancer screening is essential for early diagnosis and increased chances of cure.

Currently, most breast cancer screening uses medical imaging such as mammograms and ultrasound, which are read and diagnosed by physicians. However, this method can be inaccurate, especially in patients with dense breast tissue or other abnormalities.

The use of AI in breast cancer diagnosis is a new approach that is being developed. AI is used to analyze medical imaging results to detect breast tissue abnormalities.

Several studies have found that AI can detect breast tissue abnormalities with 99% accuracy, which is 20% higher than the current standard for breast cancer diagnosis.

Benefits of using AI to diagnose breast cancer

Using AI to diagnose breast cancer has several benefits, including:

• Helps physicians diagnose disease more accurately
• Reduces diagnostic errors
• Allows physicians to diagnose disease faster
• Allows patients to receive appropriate and timely treatment

Limitations of using AI to diagnose breast cancer

However, using AI to diagnose breast cancer still has some limitations, including:

• Requires large amounts of medical imaging data to train AI
• May be inaccurate if AI receives inaccurate medical imaging data
• Cannot yet be used to diagnose breast cancer in all cases

Trends in the use of AI to diagnose breast cancer

The use of AI to diagnose breast cancer is expected to become more popular in the future. AI has the potential to reduce diagnostic errors and help patients receive appropriate and timely treatment.

Currently, several technology companies are developing AI for breast cancer diagnosis. It is expected that AI will be approved by the U.S. Food and Drug Administration (FDA) by 2025.