Deep learning-enabled virtual histological staining of biological samples
Histological staining is the gold standard for tissue examination in clinical pathology and life-
science research, which visualizes the tissue and cellular structures using chromatic dyes or …
science research, which visualizes the tissue and cellular structures using chromatic dyes or …
Designing deep learning studies in cancer diagnostics
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients
Histopathologic assessment is indispensable for diagnosing colorectal cancer (CRC).
However, manual evaluation of the diseased tissues under the microscope cannot reliably …
However, manual evaluation of the diseased tissues under the microscope cannot reliably …
Mitosis domain generalization in histopathology images—the MIDOG challenge
The density of mitotic figures (MF) within tumor tissue is known to be highly correlated with
tumor proliferation and thus is an important marker in tumor grading. Recognition of MF by …
tumor proliferation and thus is an important marker in tumor grading. Recognition of MF by …
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology
A model's ability to express its own predictive uncertainty is an essential attribute for
maintaining clinical user confidence as computational biomarkers are deployed into real …
maintaining clinical user confidence as computational biomarkers are deployed into real …
Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare
Background: The idea of smart healthcare has gradually gained attention as a result of the
information technology industry's rapid development. Smart healthcare uses next-generation …
information technology industry's rapid development. Smart healthcare uses next-generation …
Application of artificial intelligence technology in oncology: Towards the establishment of precision medicine
Simple Summary Artificial intelligence (AI) technology has been advancing rapidly in recent
years and is being implemented in society. The medical field is no exception, and the clinical …
years and is being implemented in society. The medical field is no exception, and the clinical …
A two‐stream deep neural network‐based intelligent system for complex skin cancer types classification
Medical imaging systems installed in different hospitals and labs generate images in bulk,
which could support medics to analyze infections or injuries. Manual inspection becomes …
which could support medics to analyze infections or injuries. Manual inspection becomes …
Data drift in medical machine learning: implications and potential remedies
Data drift refers to differences between the data used in training a machine learning (ML)
model and that applied to the model in real-world operation. Medical ML systems can be …
model and that applied to the model in real-world operation. Medical ML systems can be …
A comprehensive multi-domain dataset for mitotic figure detection
The prognostic value of mitotic figures in tumor tissue is well-established for many tumor
types and automating this task is of high research interest. However, especially deep …
types and automating this task is of high research interest. However, especially deep …