[Renal biopsy and digitalization: a new era?]

Area of Science:

• Digital pathology
• Medical imaging analysis
• Nephrology

Background:

• Digital technology and AI are revolutionizing healthcare, leading to more precise and personalized medicine.
• Computational analysis is increasingly vital for interpreting biomedical data and images.
• Oncopathology has already adopted these techniques for improved diagnostics and treatment strategies.

Purpose of the Study:

• To review the advancements in image analysis within nephropathology.
• To explore the impact of computational techniques on kidney disease diagnosis and treatment.

Main Methods:

• Review of current literature on computational analysis and image processing in nephropathology.
• Analysis of emerging trends and applications of artificial intelligence in the field.

Main Results:

• Computational analysis offers significant potential for enhancing diagnostic speed and accuracy in nephropathology.
• Image analysis can refine prognoses and identify targeted therapies for kidney diseases.
• Predictive modeling for therapeutic responses is a key emerging application.

Conclusions:

• Nephropathology is poised for transformation by technological advances in image analysis.
• These innovations promise to improve patient outcomes through more precise and personalized care.
• Further integration of computational tools is expected to reshape the future of nephropathology.