Thông tin nhà nghiên cứu KH&CN

Ứng dụng AI trong chẩn đoán hình ảnh y khoa tại Việt Nam

Image-based contextual pill recognition with medical knowledge graph assistance

Enhancing deep learning-based 3-lead ecg classification with heartbeat counting and demographic data integration

Fedgrad: Mitigating backdoor attacks in federated learning through local ultimate gradients inspection

Ensemble learning of myocardial displacements for myocardial infarction detection in echocardiography

Sem: A simple yet efficient model-agnostic local training mechanism to tackle data sparsity and scarcity in federated learning

Hệ thống số hoá và nhận dạng dữ liệu cá nhân từ ảnh chụp

Hệ thống tự động lập lịch và nhắc lịch sử dụng thuốc

Hệ thống và phương pháp quản lý hình ảnh y tế

Hệ thống và phương pháp quản lý hình ảnh y tế

Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels

Phase recognition in contrast‐enhanced CT scans based on deep learning and random sampling

VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations

Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings

An accurate and explainable deep learning system improves interobserver agreement in the interpretation of chest radiograph

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese

Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks

Learning from multiple expert annotators for enhancing anomaly detection in medical image analysis

Enhancing Few-Shot Image Classification With Cosine Transformer

PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography

LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification

High accurate and explainable multi-pill detection framework with graph neural network-assisted multimodal data fusion

FedDCT: Federated learning of large convolutional neural networks on resource-constrained devices using divide and collaborative training

Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions

Personalized privacy-preserving framework for cross-silo federated learning

GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices

MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea In Classification Problem

The i-CanManage program to improve exercise and symptom management for Vietnamese women after cancer: A pilot randomized controlled trial protocol

Training-Free Condition Video Diffusion Models for Single Frame Spatial-Semantic Echocardiogram Synthesis

FedMAC: Tackling Partial-Modality Missing in Federated Learning with Cross-Modal Aggregation and Contrastive Regularization

D-SarcNet: A Dual-stream Deep Learning Framework for Automatic Analysis of Sarcomere Structures in Fluorescently Labeled hiPSC-CMs

D-SarcNet: A Dual-stream Deep Learning Framework for Automatic Analysis of Sarcomere Structures in Fluorescently Labeled hiPSC-CMs

CT to PET Translation: A Large-scale Dataset and Domain-Knowledge-Guided Diffusion Approach

FedBlock: A Blockchain Approach to Federated Learning against Backdoor Attacks

SarcNet: A Novel AI-Based Framework to Automatically Analyze and Score Sarcomere Organizations in Fluorescently Tagged HIPSC-CMS

Foundation Model and Temporal Prios-guided Transductive Few-shot Action Recognition

Bridging Classification and Segmentation in Osteosarcoma Assessment via Foundation and Discrete Diffusion Models

SEMISE: Semi-Supervised Learning for Severity Representation in Medical Image

Human sleep position classification using a lightweight model and acceleration data

SAFA: Handling Sparse and Scarce Data in Federated Learning With Accumulative Learning

BG-GAN: Generative AI Enable Representing Brain Structure-Function Connections for Alzheimer’s Disease

SG-GAN: Fine Stereoscopic-Aware Generation for 3D Brain Point Cloud Up-Sampling From a Single Image

Noisy data-based attack: A new type of untargeted attack in Federated Learning and its countermeasures

A deep learning framework for spinal lesions detection and classification from radiographs

Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks

A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms Convolutional Neural Networks

Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation

Enhancing deep learning-based 3-lead ecg classification with heartbeat counting and demographic data integration

Echocardiography video synthesis from end diastolic semantic map via diffusion model

Learning to Estimate Critical Gait Parameters from Single-View RGB Videos with Transformer-Based Attention Network

3D Point Cloud Analysis for Detection and Characterization of Defects on Airplane Exterior Surface

Phase recognition in contrast- enhanced CT scans based on deep learning and random sampling

A clinical validation of VinDr-CXR, an AI system for detecting abnormal chest radiographs

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese

PediCXR: An open, large-scale chest radiograph dataset for interpretation of thoracic diseases in children

LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification

High Accurate and Explainable Multi-Pill Detection Framework with Graph Neural Network-Assisted Multimodal Data Fusion

Learning from multiple expert annotators for enhancing anomaly detection in medical image analysis

Enhancing few-shot image classification with cosine transformer

Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions

GAMMA: A universal model for calibrating sensory data of multiple low-cost air monitoring devices

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices Using Divide and Collaborative Training

Learning to recognise 3D human action from a new skeleton‐based representation using deep convolutional neural networks

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography

Exploiting deep residual networks for human action recognition from skeletal data

Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels

VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations

Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks

Personalized privacy-preserving framework for cross-silo federated learning

Ứng dụng trí tuệ nhân tạo trong Phân tích ảnh y tế

Building large-scale medical imaging datasets for developing AI-based computer-aided de- tection/diagnosis systems.

Evaluating the Effect of Antiviral Drugs using Polarized Light Imaging and Machine Learning Approaches

Enhancing Precision Digital Pathology with an AI-powered Platform Accelerated by Super- computers

Đánh giá tác động của thuốc kháng vi-rút bằng công nghệ chụp ảnh ánh sáng phân cực kết hợp với phương pháp học máy.

Developing a unified, low-cost, self-care mobile health application for common disease screening and early detection in low-and middle-income countries

Phát triển một ứng dụng chăm sóc sức khỏe di động toàn diện, chi phí thấp, hỗ trợ tự chăm sóc cho việc sàng lọc và phát hiện sớm các bệnh phổ biến tại các quốc gia có thu nhập thấp và trung bình.

From Causal Understanding of Healthy Longevity to Smart Health

Từ hiểu biết cơ bản về tuổi thọ khỏe mạnh đến y tế thông minh.

Improving systoms for women after cancer treatment: A Trial of the i-CanMagae Applica- tion

Nghiên cứu thử nghiệm ứng dụng i-CanManage trong việc cải thiện triệu chứng ở phụ nữ sau điều trị ung thư.

VAIPE: AI-assisted IoT-enabled smart, optimal, and Protective hEalthcare monitoring and supporting system for Vietnamese.

VAIPE: Hệ thống chăm sóc sức khỏe thông minh ứng dụng AI và IoT dành cho người Việt.

Smart Life Smart Living Intercontinental. AI by and for People

Sống thông minh – Sống hiện đại toàn cầu. Trí tuệ nhân tạo vì con người và do con người.

Building large-scale medical imaging datasets for developing AI-based computer-aided de- tection/diagnosis systems.

Developing a unified, low-cost, self-care mobile health application for common disease screening and early detection in low-and middle-income countries

Enhancing Precision Digital Pathology with an AI-powered Platform Accelerated by Super- computers

Evaluating the Effect of Antiviral Drugs using Polarized Light Imaging and Machine Learning Approaches

F-rom Causal Understanding of Healthy Longevity to Smart Health

Improving systoms for women after cancer treatment: A Trial of the i-CanMagae Applica- tion

Smart Life Smart Living Intercontinental. AI by and for People

Ứng dụng trí tuệ nhân tạo trong Phân tích ảnh y tế

VAIPE: AI-assisted IoT-enabled smart, optimal, and Protective hEalthcare monitoring and supporting system for Vietnamese.