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Pathology

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Introduction to Artificial Intelligence and Machine Learning for Pathology.

Archives of pathology & laboratory medicine
CONTEXT.—: Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and ou...

Perspectives in pathomics in head and neck cancer.

Current opinion in oncology
PURPOSE OF REVIEW: Pathology is the cornerstone of cancer care. Pathomics, which represents the use of artificial intelligence in digital pathology, is an emerging and promising field that will revolutionize medical and surgical pathology in the comi...

Pathomics in urology.

Current opinion in urology
PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summariz...

Artificial Intelligence in Pathology: A Simple and Practical Guide.

Advances in anatomic pathology
Artificial intelligence (AI) is having an increasing impact on the field of pathology, as computation techniques allow computers to perform tasks previously performed by people. Here, we offer a simple and practical guide to AI methods used in pathol...

Implementing Deep Learning Algorithms in Anatomic Pathology Using Open-source Deep Learning Libraries.

Advances in anatomic pathology
The application of artificial intelligence technologies to anatomic pathology has the potential to transform the practice of pathology, but, despite this, many pathologists are unfamiliar with how these models are created, trained, and evaluated. In ...

Explainable AI (xAI) for Anatomic Pathology.

Advances in anatomic pathology
Pathologists are adopting whole slide images (WSIs) for diagnosis, thanks to recent FDA approval of WSI systems as class II medical devices. In response to new market forces and recent technology advances outside of pathology, a new field of computat...

Deep representation learning for domain adaptable classification of infrared spectral imaging data.

Bioinformatics (Oxford, England)
MOTIVATION: Applying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which...

[Recent Developments in a Automated Diagnosis of Pathological Images and Three-dimensional Histopathology].

Brain and nerve = Shinkei kenkyu no shinpo
Rapid improvements in computing power are advancing machine learning technology using neural networks, revolutionizing the field of image analysis and allowing for automated diagnosis of pathological images. In addition, the recent development of tis...

Digital pathology and artificial intelligence.

The Lancet. Oncology
In modern clinical practice, digital pathology has a crucial role and is increasingly a technological requirement in the scientific laboratory environment. The advent of whole-slide imaging, availability of faster networks, and cheaper storage soluti...