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 …
Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Deep learning has demonstrated remarkable performance across various tasks in medical
imaging. However, these approaches primarily focus on supervised learning, assuming that …
imaging. However, these approaches primarily focus on supervised learning, assuming that …
Multi-source unsupervised domain adaptation via pseudo target domain
CX Ren, YH Liu, XW Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Multi-source domain adaptation (MDA) aims to transfer knowledge from multiple source
domains to an unlabeled target domain. MDA is a challenging task due to the severe …
domains to an unlabeled target domain. MDA is a challenging task due to the severe …
Automated classification of acute leukemia on a heterogeneous dataset using machine learning and deep learning techniques
Today, artificial intelligence and deep learning techniques constitute a prominent part in the
area of medical sciences. These techniques help doctors detect diseases early and reduce …
area of medical sciences. These techniques help doctors detect diseases early and reduce …
Advancing instance segmentation and WBC classification in peripheral blood smear through domain adaptation: A study on PBC and the novel RV-PBS datasets
JB Pal, A Bhattacharyea, D Banerjee… - Expert Systems with …, 2024 - Elsevier
Automating blood cell counting and detection from smear slides holds significant potential
for aiding doctors in disease diagnosis through blood tests. However, existing literature has …
for aiding doctors in disease diagnosis through blood tests. However, existing literature has …
A distribution information sharing federated learning approach for medical image data
L Zhao, J Huang - Complex & Intelligent Systems, 2023 - Springer
In recent years, federated learning has been believed to play a considerable role in cross-
silo scenarios (eg, medical institutions) due to its privacy-preserving properties. However …
silo scenarios (eg, medical institutions) due to its privacy-preserving properties. However …
Degpr: Deep guided posterior regularization for multi-class cell detection and counting
AK Tyagi, C Mohapatra, P Das… - Proceedings of the …, 2023 - openaccess.thecvf.com
Multi-class cell detection and counting is an essential task for many pathological diagnoses.
Manual counting is tedious and often leads to inter-observer variations among pathologists …
Manual counting is tedious and often leads to inter-observer variations among pathologists …
On the effectiveness of leukocytes classification methods in a real application scenario
Automating the analysis of digital microscopic images to identify the cell sub-types or the
presence of illness has assumed a great importance since it aids the laborious manual …
presence of illness has assumed a great importance since it aids the laborious manual …
Leukocyte classification using relative-relationship-guided contrastive learning
Hematologic diseases and blood disorders can be studied through microscopic examination
of blood smear images or chemical assays. Many researchers are focused on utilizing deep …
of blood smear images or chemical assays. Many researchers are focused on utilizing deep …
Cycle consistent twin energy-based models for image-to-image translation
Abstract Domain shift refers to change of distributional characteristics between the training
(source) and the testing (target) datasets of a learning task, leading to performance drop. For …
(source) and the testing (target) datasets of a learning task, leading to performance drop. For …