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Biopsy

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Artificial intelligence applications for pre-implantation kidney biopsy pathology practice: a systematic review.

Journal of nephrology
BACKGROUND: Transplant nephropathology is a highly specialized field of pathology comprising both the evaluation of organ donor biopsy for organ allocation and post-transplant graft biopsy for assessment of rejection or graft damage. The introduction...

Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Distinguishing gastric epithelial regeneration change from dysplasia and histopathological diagnosis of dysplasia is subject to interobserver disagreement in endoscopic specimens. In this study, we developed a method to distinguish gastri...

Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease.

Scientific reports
Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discov...

Diagnosis of significant liver fibrosis in patients with chronic hepatitis B using a deep learning-based data integration network.

Hepatology international
BACKGROUND AND AIMS: Chronic hepatitis B virus (CHB) infection remains a major global health burden and the non-invasive and accurate diagnosis of significant liver fibrosis (≥ F2) in CHB patients is clinically very important. This study aimed to ass...

Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies.

Nature medicine
Endomyocardial biopsy (EMB) screening represents the standard of care for detecting allograft rejections after heart transplant. Manual interpretation of EMBs is affected by substantial interobserver and intraobserver variability, which often leads t...

The role of MRI in prostate cancer: current and future directions.

Magma (New York, N.Y.)
There has been an increasing role of magnetic resonance imaging (MRI) in the management of prostate cancer. MRI already plays an essential role in the detection and staging, with the introduction of functional MRI sequences. Recent advancements in ra...

Application of a Deep-Learning Technique to Non-Linear Images From Human Tissue Biopsies for Shedding New Light on Breast Cancer Diagnosis.

IEEE journal of biomedical and health informatics
The development of label-free non-destructive techniques to be used as diagnostic tools in cancer research is of great importance for improving the quality of life for millions of patients. Previous studies have demonstrated that Third Harmonic Gener...

The association between perineural invasion in mpMRI-targeted and/or systematic prostate biopsy and adverse pathological outcomes in robot-assisted radical prostatectomy.

Actas urologicas espanolas
INTRODUCTION AND OBJECTIVES: This study aims to investigate the relationship between perineural invasion (PNI) in targeted (TBx) and/or systematic (SBx) prostate needle biopsy and adverse pathological features of prostate cancer (PCa) in prostatectom...

Artificial intelligence outperforms standard blood-based scores in identifying liver fibrosis patients in primary care.

Scientific reports
For years, hepatologists have been seeking non-invasive methods able to detect significant liver fibrosis. However, no previous algorithm using routine blood markers has proven to be clinically appropriate in primary care. We present a novel approach...