Pathology

Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms.

BACKGROUND & AIMS: The Banff Liver Working Group recently published consensus recommendations for steatosis assessment in donor liver biopsy, but few studies reported their use and no automated deep-learning algorithms based on the proposed criteria have been developed so far. We evaluated Banff recommendations on a large monocentric series of donor liver needle biopsies by comparing pathologists'...

ChatGPT as an aid for pathological diagnosis of cancer.

Diagnostic workup of cancer patients is highly reliant on the science of pathology using cytopathology, histopathology, and other ancillary techniques like immunohistochemistry and molecular cytogenetics. Data processing and learning by means of artificial intelligence (AI) has become a spearhead for the advancement of medicine, with pathology and laboratory medicine being no exceptions. ChatGPT, ...

Enhancing diagnosis of Hirschsprung's disease using deep learning from histological sections of post pull-through specimens: preliminary results.

PURPOSE: Accurate histological diagnosis in Hirschsprung disease (HD) is challenging, due to its complexity and potential for errors. In this study, w...

Opportunities and challenges for deep learning in cell dynamics research.

The growth of artificial intelligence (AI) has led to an increase in the adoption of computer vision and deep learning (DL) techniques for the evaluat...

Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has reached epidemic proportions worldwide and is the most frequent cause of chronic live...

Wavelet scattering networks in deep learning for discovering protein markers in a cohort of Swedish rectal cancer patients.

BACKGROUND: Cancer biomarkers play a pivotal role in the diagnosis, prognosis, and treatment response prediction of the disease. In this study, we ana...

Deep-qGFP: A Generalist Deep Learning Assisted Pipeline for Accurate Quantification of Green Fluorescent Protein Labeled Biological Samples in Microreactors.

Absolute quantification of biological samples provides precise numerical expression levels, enhancing accuracy, and performance for rare templates. Cu...

Rapid diagnosis of cervical cancer based on serum FTIR spectroscopy and support vector machines.

Cervical cancer is one of the most common malignant tumors among female gynecological diseases. This paper aims to explore the feasibility of utilizin...

What are the most relevant publications in Clinical Microbiology in the last two years?

This minireview describes some of the articles published in the last two years related to innovative technologies including CRISPR-Cas, surface-enhanc...

: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.

INTRODUCTION: Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 247 million cases reported worldwide in 2021 accord...

Investigation of latent representation of toxicopathological images extracted by CNN model for understanding compound properties in vivo.

Toxicopathological images acquired during safety assessment elucidate an individual's biological responses to a given compound, and their numerization...

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

BACKGROUND: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification rem...

AI-assisted system improves the work efficiency of cytologists via excluding cytology-negative slides and accelerating the slide interpretation.

Given the shortage of cytologists, women in low-resource regions had inequitable access to cervical cytology which plays an pivotal role in cervical c...

Application of artificial intelligence techniques for non-alcoholic fatty liver disease diagnosis: A systematic review (2005-2023).

BACKGROUND AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is a common liver disease with a rapidly growing incidence worldwide. For prognos...

Advances in melanoma: epidemiology, diagnosis, and prognosis.

Unraveling the multidimensional complexities of melanoma has required concerted efforts by dedicated community of researchers and clinicians battling ...

A Semi-Autonomous Stereotactic Brain Biopsy Robotic System With Enhanced Surgical Safety and Surgeon-Robot Collaboration.

OBJECTIVE: Despite benefits brought by recent neurosurgical robots, surgical safety and surgeon-robot collaboration remain significant challenges. In ...

[Multistain deep learning as a prognostic and predictive biomarker in colorectal cancer].

The tumor immune microenvironment (TIME) plays a crucial prognostic and predictive role in solid malignancies such as colorectal cancer (CRC). Neverth...

Shedding Light on Colorectal Cancer: An In Vivo Raman Spectroscopy Approach Combined with Deep Learning Analysis.

Raman spectroscopy has emerged as a powerful tool in medical, biochemical, and biological research with high specificity, sensitivity, and spatial and...

Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology.

Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, s...

ENAS-B: Combining ENAS With Bayesian Optimization for Automatic Design of Optimal CNN Architectures for Breast Lesion Classification From Ultrasound Images.

Efficient Neural Architecture Search (ENAS) is a recent development in searching for optimal cell structures for Convolutional Neural Network (CNN) de...