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

Continuous Glucose Monitoring and Personalized Nutrition in Type 2 Diabetes - A Scoping Review.

Studies in health technology and informatics·2026

Same authorSame journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026

Same authorSame journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026

Same author

Experimentally validated dual-band GHz metamaterial perfect absorber biosensor with negative-index response and AI-assisted electromagnetic analysis for breast cancer dielectric discrimination.

Biosensors & bioelectronics·2026

Same author

Living with spinal cord injury in the community of Bangladesh: a comprehensive analysis using the ICF framework.

Journal of rehabilitation medicine·2026

Same author

A compact triple wideband mimo antenna for microwave, ku, and mm-wave band applications of 5g wireless communication.

PloS one·2026

Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026

Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026

Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026

Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Oct 5, 2025

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Published on: March 5, 2018

ALLD: Acute Lymphoblastic Leukemia Detector.

Saleh Musleh¹, Mohammad Tariqul Islam², Mohammad Towfik Alam³

¹College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

Studies in Health Technology and Informatics

|January 22, 2022

Summary

This summary is machine-generated.

Early detection of Acute Lymphoblastic Leukemia (ALL) is crucial. A new deep learning model, ALL Detector (ALLD), accurately identifies ALL patients from microscopic images, improving early diagnosis and reducing fatality rates.

Keywords:

Acute lymphoblastic leukemia Computer aided diagnosis (CAD)Deep learning Leukemia

More Related Videos

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

Published on: July 20, 2016

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Published on: March 26, 2018

Related Experiment Videos

Last Updated: Oct 5, 2025

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

Published on: March 5, 2018

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

Published on: July 20, 2016

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Published on: March 26, 2018

Area of Science:

Oncology
Medical Imaging
Artificial Intelligence

Background:

Acute Lymphoblastic Leukemia (ALL) presents a high mortality rate.
Early detection of ALL is critical for improving patient outcomes and diagnostic strategies.

Purpose of the Study:

To develop a deep learning-based network, the ALL Detector (ALLD), for distinguishing ALL patients from healthy individuals.
To evaluate the performance of ALLD against existing diagnostic tools.

Main Methods:

Development of a deep learning network (ALLD) utilizing microscopic images of blast cells.
Evaluation of various deep learning models, with a ResNet-based model showing superior performance.
Comparative analysis of ALLD against state-of-the-art diagnostic tools.

Main Results:

The ResNet-based ALLD model achieved 98% accuracy in classifying ALL.
ALLD demonstrated superior performance compared to existing state-of-the-art tools for ALL detection.

Conclusions:

The ALL Detector (ALLD) shows significant potential in supporting pathologists for early ALL diagnosis.
Implementation of ALLD can reduce the burden on clinical practice and improve patient survival rates.