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Found 27 papers, 4 papers with code
Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review
Recent advancements in machine learning (ML) and deep learning (DL), particularly through the introduction of foundational models (FMs), have significantly enhanced surgical scene understanding within minimally invasive surgery (MIS).
Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription
Firstly, we present a comprehensive survey of the current state-of-the-art open-source healthcare LLMs and AIFMs and introduce a taxonomy of these open AIFMs, categorizing their utility across various healthcare tasks.
Temporal Graph MLP Mixer for Spatio-Temporal Forecasting
Spatiotemporal forecasting is critical in applications such as traffic prediction, climate modeling, and environmental monitoring.
Deep Reinforcement Learning Optimized Intelligent Resource Allocation in Active RIS-Integrated TN-NTN Networks
This work explores the deployment of active reconfigurable intelligent surfaces (A-RIS) in integrated terrestrial and non-terrestrial networks (TN-NTN) while utilizing coordinated multipoint non-orthogonal multiple access (CoMP-NOMA).
REFOL: Resource-Efficient Federated Online Learning for Traffic Flow Forecasting
Therefore, we propose a novel method named Resource-Efficient Federated Online Learning (REFOL) for TFF, which guarantees prediction performance in a communication-lightweight and computation-efficient way.
Real-time and Downtime-tolerant Fault Diagnosis for Railway Turnout Machines (RTMs) Empowered with Cloud-Edge Pipeline Parallelism
In this paper, an edge-cloud collaborative early-warning system is proposed to enable real-time and downtime-tolerant fault diagnosis of RTMs, providing a new paradigm for the deployment of models in safety-critical scenarios.
Natural Language Processing for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review
This review addresses gaps in the existing literature by providing a broader perspective than previous studies focused on specific cancer types or applications.
Enhancing 3D Human Pose Estimation Amidst Severe Occlusion with Dual Transformer Fusion
In the field of 3D Human Pose Estimation from monocular videos, the presence of diverse occlusion types presents a formidable challenge.
MedISure: Towards Assuring Machine Learning-based Medical Image Classifiers using Mixup Boundary Analysis
Machine learning (ML) models are becoming integral in healthcare technologies, presenting a critical need for formal assurance to validate their safety, fairness, robustness, and trustworthiness.
Multivessel Coronary Artery Segmentation and Stenosis Localisation using Ensemble Learning
This study introduces an end-to-end machine learning solution developed as part of our solution for the MICCAI 2023 Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs (ARCADE) challenge, which aims to benchmark solutions for multivessel coronary artery segmentation and potential stenotic lesion localisation from X-ray coronary angiograms.
Ranked #3 on
Coronary Artery Segmentation
on ARCADE
Robust Surgical Tools Detection in Endoscopic Videos with Noisy Data
In this paper, we propose a systematic methodology for developing robust models for surgical tool detection using noisy data.
Surgical tool classification and localization: results and methods from the MICCAI 2022 SurgToolLoc challenge
Unfortunately, obtaining the annotations needed to train machine learning models to identify and localize surgical tools is a difficult task.
Can We Revitalize Interventional Healthcare with AI-XR Surgical Metaverses?
Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science.
Communication and Control in Collaborative UAVs: Recent Advances and Future Trends
The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains.
Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges
Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting.
Early Risk Prediction of Chronic Myeloid Leukemia with Protein Sequences using Machine Learning-based Meta-Ensemble
In the study, we developed a multi-layer-perception-based meta-ensemble system using protein amino acid sequences for early risk prediction of CML.
Comparative Analysis of Time Series Forecasting Approaches for Household Electricity Consumption Prediction
Secondly, we also implemented time series forecasting models, ARIMA and VAR, in python to forecast household energy consumption of selected South Korean households with and without weather data.
Measuring Novelty in Autonomous Vehicles Motion Using Local Outlier Factor Algorithm
Under unexpected conditions or scenarios, autonomous vehicles (AV) are more likely to follow abnormal unplanned actions, due to the limited set of rules or amount of experience they possess at that time.
Use of Transfer Learning and Wavelet Transform for Breast Cancer Detection
Breast cancer is one of the most common cause of deaths among women.
On the Impact of Device and Behavioral Heterogeneity in Federated Learning
Federated learning (FL) is becoming a popular paradigm for collaborative learning over distributed, private datasets owned by non-trusting entities.
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation
The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs).
Amateur Drones Detection: A machine learning approach utilizing the acoustic signals in the presence of strong interference
Owing to small size, sensing capabilities and autonomous nature, the Unmanned Air Vehicles (UAVs) have enormous applications in various areas, e. g., remote sensing, navigation, archaeology, journalism, environmental science, and agriculture.
Classification of Chest Diseases using Wavelet Transforms and Transfer Learning
Chest X-ray scan is a most often used modality by radiologists to diagnose many chest related diseases in their initial stages.
Secure and Robust Machine Learning for Healthcare: A Survey
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images.
Crowd Density Estimation using Novel Feature Descriptor
Crowd density estimation is an important task for crowd monitoring.
A deep learning approach for analyzing the composition of chemometric data
We trained L2 regularized sparse autoencoder end-to-end for reducing the size of the feature vector to handle the classic problem of the curse of dimensionality in chemometric data analysis.
A Review of Internet of Things Architecture, Technologies and Analysis Smartphone-based Attacks Against 3D printers
It has been difficult to ignore the importance of the IoT field with the new development of applications such as a smartphone in the present era.
Networking and Internet Architecture
