AIMC Topic: Histology

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Registered multi-device/staining histology image dataset for domain-agnostic machine learning models.

Scientific data Apr 3, 2024
Variations in color and texture of histopathology images are caused by differences in staining conditions and imaging devices between hospitals. These biases decrease the robustness of machine learning models exposed to out-of-domain data. To address...
Humans Neural Networks, Computer Histological Techniques Histology Eosine Yellowish-(YS) Machine Learning Image Processing, Computer-Assisted Staining and Labeling
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Comparing the performance of artificial intelligence learning models to medical students in solving histology and embryology multiple choice questions.

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft Mar 21, 2024
INTRODUCTION: The appearance of artificial intelligence language models (AI LMs) in the form of chatbots has gained a lot of popularity worldwide, potentially interfering with different aspects of education, including medical education as well. The p...
Embryology Educational Measurement Education, Medical, Undergraduate Histology Humans Artificial Intelligence Students, Medical
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Validating instructional design and predicting student performance in histology education: Using machine learning via virtual microscopy.

Anatomical sciences education Oct 7, 2023
As a part of modern technological environments, virtual microscopy enriches histological learning, with support from large institutional investments. However, existing literature does not supply empirical evidence of its role in improving pedagogy. V...
Algorithms Learning Female Humans Machine Learning Curriculum Computer-Assisted Instruction Histology Students, Medical User-Computer Interface Male Educational Measurement Microscopy
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High-Order Correlation-Guided Slide-Level Histology Retrieval With Self-Supervised Hashing.

IEEE transactions on pattern analysis and machine intelligence Aug 7, 2023
Histopathological Whole Slide Images (WSIs) play a crucial role in cancer diagnosis. It is of significant importance for pathologists to search for images sharing similar content with the query WSI, especially in the case-based diagnosis. While slide...
Datasets as Topic Pattern Recognition, Automated Pathology Unsupervised Machine Learning Supervised Machine Learning Image Interpretation, Computer-Assisted Histology Humans Algorithms Neoplasms Cluster Analysis
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Handcrafted Histological Transformer (H2T): Unsupervised representation of whole slide images.

Medical image analysis Jan 19, 2023
Diagnostic, prognostic and therapeutic decision-making of cancer in pathology clinics can now be carried out based on analysis of multi-gigapixel tissue images, also known as whole-slide images (WSIs). Recently, deep convolutional neural networks (CN...
Neural Networks, Computer Humans Histology
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Resolution-based distillation for efficient histology image classification.

Artificial intelligence in medicine Aug 6, 2021
Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the computing pipeline. This paper proposes a novel deep learning-based method...
Histology Celiac Disease Carcinoma, Renal Cell Humans Adenocarcinoma of Lung Machine Learning Deep Learning Lung Neoplasms Kidney Neoplasms
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Identifying transcriptomic correlates of histology using deep learning.

PloS one Nov 25, 2020
Linking phenotypes to specific gene expression profiles is an extremely important problem in biology, which has been approached mainly by correlation methods or, more fundamentally, by studying the effects of gene perturbations. However, genome-wide ...
Histology Humans Neoplasm Proteins Tissue Distribution Neoplasms Transcriptome Genome Deep Learning Gene Expression Regulation, Neoplastic
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Impact of pre-analytical variables on deep learning accuracy in histopathology.

Histopathology May 16, 2019
AIMS: Machine learning (ML) binary classification in diagnostic histopathology is an area of intense investigation. Several assumptions, including training image quality/format and the number of training images required, appear to be similar in many ...
Image Interpretation, Computer-Assisted Histological Techniques Pathology, Clinical Histology Male Machine Learning Diagnosis, Computer-Assisted Humans Female Deep Learning Neural Networks, Computer
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A dense multi-path decoder for tissue segmentation in histopathology images.

Computer methods and programs in biomedicine Mar 14, 2019
BACKGROUND AND OBJECTIVE: Segmenting different tissue components in histopathological images is of great importance for analyzing tissues and tumor environments. In recent years, an encoder-decoder family of convolutional neural networks has increasi...
Image Processing, Computer-Assisted Area Under Curve Prostate Humans Male Breast Algorithms Histology Neural Networks, Computer ROC Curve Epithelium Female Software Pattern Recognition, Automated Reproducibility of Results
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Deep learning nuclei detection: A simple approach can deliver state-of-the-art results.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 17, 2018
BACKGROUND: Deep convolutional neural networks have become a widespread tool for the detection of nuclei in histopathology images. Many implementations share a basic approach that includes generation of an intermediate map indicating the presence of ...
Algorithms Image Interpretation, Computer-Assisted Deep Learning Cell Nucleus Histology
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