Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Trends and disparities in valvular heart disease-related mortality among adults with diabetes mellitus in the United States: 1999-2024.

Journal of diabetes and metabolic disorders·2026

Same author

Predictive Role of Triglyceride-to-High-Density Lipoprotein-Cholesterol Ratio and Triglyceride-Glucose Index in Glycaemic Control among Type 2 Diabetes Mellitus Patients with Chronic Kidney Disease.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP·2026

Same author

Integration of temporal patterns, genotypic response, and environmental-determinants on aphid infestation in wheat.

Bulletin of entomological research·2026

Same author

Impact of Pre-Transplant Depth of Response on Outcomes in Patients With Multiple Myeloma: A Report on Behalf of Pakistan Blood and Marrow Transplant Group.

Asia-Pacific journal of clinical oncology·2026

Same author

Does Tumor Grade Have any Prognostic Significance in Chromophobe Renal Cell Carcinoma: A Clinicopathological Study.

Journal of cancer & allied specialties·2026

Same author

Chlorantraniliprole Resistance and Associated Fitness Costs in Fall Armyworm (<i>Spodoptera frugiperda</i>): Implications for Resistance Management.

Insects·2025

Same journal

Machine learning-based prediction of dataset-defined myocardial infarction risk: A retrospective computational study for precision cardiovascular risk assessment.

Digital health·2026

Same journal

Visualization of artificial intelligence applications in oral disease diagnosis: A bibliometric analysis.

Digital health·2026

Same journal

Wearable IoT health sensing beyond functional utility: Identity-expressive and hedonic determinants of user acceptance in intimate physiological monitoring devices - A sequential FA-ANP mixed-methods investigation with digital health policy implications.

Digital health·2026

Same journal

Heterogeneity of information across seven curated national or international digital health app repositories.

Digital health·2026

Same journal

Interpretable machine learning for early prediction of acute kidney injury in critically ill patients with acute pancreatitis.

Digital health·2026

Same journal

Exploring perceptions of data risks in AI-enabled nursing research: A qualitative study.

Digital health·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 25, 2025

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

Toward interpretable and generalized mitosis detection in digital pathology using deep learning.

Hasan Farooq¹, Saira Saleem², Iffat Aleem²

¹Computational Biology Research Lab, National University of Computer & Emerging Sciences, Islamabad, Pakistan.

|May 23, 2024

Summary

This summary is machine-generated.

This study introduces a novel deep learning method for accurate mitosis detection in cancer diagnosis. The approach demonstrates strong performance and generalizability across datasets, aiding digital pathology adoption.

Keywords:

Mitosis detection deep learning digital pathology generalizability interpretable AI

More Related Videos

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Related Experiment Videos

Last Updated: Jun 25, 2025

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Analyzing Mitochondrial Morphology Through Simulation Supervised Learning

Published on: March 3, 2023

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Area of Science:

Computational pathology
Medical image analysis
Deep learning applications in oncology

Background:

Mitotic activity index is crucial for cancer prognosis.
Accurate mitosis detection is challenging due to microscopic nuclei, partial labeling, and class imbalance.

Purpose of the Study:

To address challenges in current mitosis detection pipelines.
To propose a novel deep learning method for accurate mitotic nuclei prediction.

Main Methods:

Utilized the MiDoG'22 dataset for training, validation, and testing.
Applied deep learning inspired by recent research and extensive dataset analysis.
Validated the methodology on the TUPAC'16 dataset and a real-time clinical case.

Main Results:

Achieved an F1-score of 0.87 on the MiDoG'22 dataset.
Obtained an F1-score of 0.83 on the TUPAC'16 dataset.
Demonstrated quantitative and qualitative promising results.

Conclusions:

The proposed methodology is accurate, generalizable, and interpretable.
It shows potential for speeding up computer-aided digital pathology adoption in clinical settings.