Prevention of medical errors

ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention

Linear attention mechanisms deliver significant advantages for Large Language Models (LLMs) by providing linear computational complexity, enabling efficient processing of ultra-long sequences (e.g., 1M context). However, existing Sequence Parallelism (SP) methods, essential for distributing these workloads across devices, become the primary bottleneck due to substantial communication overhead. I...

Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.

Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reducing the risk of misdiagnosis associated with conventional methods. The aim of this meta-analysis is to evaluate the overall classification accuracy of...

PrivCore: Multiplication-activation co-reduction for efficient private inference.

The marriage of deep neural network (DNN) and secure 2-party computation (2PC) enables private inference (PI) on the encrypted client-side data and se...

Learn the global prompt in the low-rank tensor space for heterogeneous federated learning.

Federated learning collaborates with multiple clients to train a global model, enhancing the model generalization while allowing the local data transm...

ADAMT: Adaptive distributed multi-task learning for efficient image recognition in Mobile Ad-hoc Networks.

Distributed machine learning in mobile adhoc networks faces significant challenges due to the limited computational resources of devices, non-IID data...

Feature-Tuning Hierarchical Transformer via token communication and sample aggregation constraint for object re-identification.

Recently, transformer-based methods have shown remarkable success in object re-identification. However, most works directly embed off-the-shelf transf...

EEG-Based Auditory BCI for Communication in a Completely Locked-In Patient Using Volitional Frequency Band Modulation

Patients with amyotrophic lateral sclerosis (ALS) in the completely locked-in state (CLIS) can lose all reliable motor control and are left without ...

A Novel Frame Identification and Synchronization Technique for Smartphone Visible Light Communication Systems Based on Convolutional Neural Networks

This paper proposes a novel, robust, and lightweight supervised Convolutional Neural Network (CNN)-based technique for frame identification and sync...

Equitable Federated Learning with NCA

Federated Learning (FL) is enabling collaborative model training across institutions without sharing sensitive patient data. This approach is partic...

Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine

Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in ado...

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things

Recent developments in the Internet of Bio-Nano Things (IoBNT) are laying the groundwork for innovative applications across the healthcare sector. N...

MS-IQA: A Multi-Scale Feature Fusion Network for PET/CT Image Quality Assessment

Positron Emission Tomography / Computed Tomography (PET/CT) plays a critical role in medical imaging, combining functional and anatomical informatio...

[Association between gut microbiota and hyperuricemia: insights into innovative therapeutic strategies].

Uric acid (UA) is the final metabolite of purines in the human body. An imbalance in UA production and excretion that disrupts homeostasis leads to el...

Systems-Theoretic and Data-Driven Security Analysis in ML-enabled Medical Devices

The integration of AI/ML into medical devices is rapidly transforming healthcare by enhancing diagnostic and treatment facilities. However, this adv...

HARMONY: A Scalable Distributed Vector Database for High-Throughput Approximate Nearest Neighbor Search

Approximate Nearest Neighbor Search (ANNS) is essential for various data-intensive applications, including recommendation systems, image retrieval, ...

VisText-Mosquito: A Multimodal Dataset and Benchmark for AI-Based Mosquito Breeding Site Detection and Reasoning

Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreaks. In ...

Movable Antennas Meet Low-Altitude Wireless Networks: Fundamentals, Opportunities, and Future Directions

With the rapid development of low-altitude applications, there is an increasing demand for low-altitude wireless networks (LAWNs) to simultaneously ...

A multimodal deep learning model for detecting endoscopic images of near-infrared fluorescence capsules.

Early screening for gastrointestinal (GI) diseases is critical for preventing cancer development. With the rapid advancement of deep learning technolo...

SecONNds: Secure Outsourced Neural Network Inference on ImageNet

The widespread adoption of outsourced neural network inference presents significant privacy challenges, as sensitive user data is processed on untru...

Toward Low-Altitude Airspace Management and UAV Operations: Requirements, Architecture and Enabling Technologies

The low-altitude economy (LAE) is rapidly advancing toward intelligence, connectivity, and coordination, bringing new challenges in dynamic airspace...