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Latest AI and machine learning research in surveys for healthcare professionals.

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A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments

Model Extraction Attacks (MEAs) threaten modern machine learning systems by enabling adversaries to steal models, exposing intellectual property and training data. With the increasing deployment of machine learning models in distributed computing environments, including cloud, edge, and federated learning settings, each paradigm introduces distinct vulnerabilities and challenges. Without a unifi...

Autonomous Agricultural Monitoring with Aerial Drones and RF Energy-Harvesting Sensor Tags

In precision agriculture and plant science, there is an increasing demand for wireless sensors that are easy to deploy, maintain, and monitor. This paper investigates a novel approach that leverages recent advances in extremely low-power wireless communication and sensing, as well as the rapidly increasing availability of unmanned aerial vehicle (UAV) platforms. By mounting a specialized wireles...

A Comprehensive Survey on the Trustworthiness of Large Language Models in Healthcare

The application of large language models (LLMs) in healthcare has the potential to revolutionize clinical decision-making, medical research, and pat...

Robust Bias Detection in MLMs and its Application to Human Trait Ratings

There has been significant prior work using templates to study bias against demographic attributes in MLMs. However, these have limitations: they ov...

Fundamental Survey on Neuromorphic Based Audio Classification

Audio classification is paramount in a variety of applications including surveillance, healthcare monitoring, and environmental analysis. Traditiona...

CER: Confidence Enhanced Reasoning in LLMs

Ensuring the reliability of Large Language Models (LLMs) in complex reasoning tasks remains a formidable challenge, particularly in scenarios that d...

GenAI at the Edge: Comprehensive Survey on Empowering Edge Devices

Generative Artificial Intelligence (GenAI) applies models and algorithms such as Large Language Model (LLM) and Foundation Model (FM) to generate ne...

CardiacMamba: A Multimodal RGB-RF Fusion Framework with State Space Models for Remote Physiological Measurement

Heart rate (HR) estimation via remote photoplethysmography (rPPG) offers a non-invasive solution for health monitoring. However, traditional single-...

Discovering the influence of personal features in psychological processes using Artificial Intelligence techniques: the case of COVID19 lockdown in Spain

At the end of 2019, an outbreak of a novel coronavirus was reported in China, leading to the COVID-19 pandemic. In Spain, the first cases were detec...

User Intent to Use DeepSeek for Healthcare Purposes and their Trust in the Large Language Model: Multinational Survey Study

Large language models (LLMs) increasingly serve as interactive healthcare resources, yet user acceptance remains underexplored. This study examines ...

Personalized Image Generation with Deep Generative Models: A Decade Survey

Recent advancements in generative models have significantly facilitated the development of personalized content creation. Given a small set of image...

Towards Equitable AI: Detecting Bias in Using Large Language Models for Marketing

The recent advances in large language models (LLMs) have revolutionized industries such as finance, marketing, and customer service by enabling soph...

From Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval

Discrete tokenizers have emerged as indispensable components in modern machine learning systems, particularly within the context of autoregressive m...

A Comprehensive Survey on Concept Erasure in Text-to-Image Diffusion Models

Text-to-Image (T2I) models have made remarkable progress in generating high-quality, diverse visual content from natural language prompts. However, ...

InTec: integrated things-edge computing: a framework for distributing machine learning pipelines in edge AI systems

With the rapid expansion of the Internet of Things (IoT), sensors, smartphones, and wearables have become integral to daily life, powering smart app...

Biases in Edge Language Models: Detection, Analysis, and Mitigation

The integration of large language models (LLMs) on low-power edge devices such as Raspberry Pi, known as edge language models (ELMs), has introduced...

A Survey of LLM-based Agents in Medicine: How far are we from Baymax?

Large Language Models (LLMs) are transforming healthcare through the development of LLM-based agents that can understand, reason about, and assist w...

Setting the Course, but Forgetting to Steer: Analyzing Compliance with GDPR's Right of Access to Data by Instagram, TikTok, and YouTube

The comprehensibility and reliability of data download packages (DDPs) provided under the General Data Protection Regulation's (GDPR) right of acces...

A Survey of Large Language Models in Psychotherapy: Current Landscape and Future Directions

Mental health remains a critical global challenge, with increasing demand for accessible, effective interventions. Large language models (LLMs) offe...

A Critical Review of Predominant Bias in Neural Networks

Bias issues of neural networks garner significant attention along with its promising advancement. Among various bias issues, mitigating two predomin...

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