Public Health & Policy

Military Medicine

Latest AI and machine learning research in military medicine for healthcare professionals.

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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of the most common mental disorders. Early mental disorder detection can reduce costs for public health agencies and prevent other major comorbidities. Additionally, the shortage of specialized personnel is very concerning since depression diagnosis is highly dependent on expert professionals and is tim...

Jan 1 2025 40435349

Hybrid deep learning model for accurate and efficient android malware detection using DBN-GRU.

The rapid growth of Android applications has led to an increase in security threats, while traditional detection methods struggle to combat advanced malware, such as polymorphic and metamorphic variants. To address these challenges, this study introduces a hybrid deep learning model (DBN-GRU) that integrates Deep Belief Networks (DBN) for static analysis and Gated Recurrent Units (GRU) for dynamic...

Jan 1 2025 40388500
Digital transformation in healthcare management: from Artificial Intelligence to blockchain.

The digital transformation of healthcare is revolutionizing the management of medical institutions, improving operational efficiency, patient outcomes...

Jan 1 2025 40219885
xSRL: Safety-Aware Explainable Reinforcement Learning -- Safety as a Product of Explainability

Reinforcement learning (RL) has shown great promise in simulated environments, such as games, where failures have minimal consequences. However, the...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, making accurate and objective diagnosis challenging w...

Dec 25 2024 40000199
LSAQ: Layer-Specific Adaptive Quantization for Large Language Model Deployment

As Large Language Models (LLMs) demonstrate exceptional performance across various domains, deploying LLMs on edge devices has emerged as a new tren...

A Machine Learning Approach for Emergency Detection in Medical Scenarios Using Large Language Models

The rapid identification of medical emergencies through digital communication channels remains a critical challenge in modern healthcare delivery, p...

Artificial Intelligence in Mental Health and Well-Being: Evolution, Current Applications, Future Challenges, and Emerging Evidence

Artificial Intelligence (AI) is a broad field that is upturning mental health care in many ways, from addressing anxiety, depression, and stress to ...

MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents

Physical adversarial attacks in driving scenarios can expose critical vulnerabilities in visual perception models. However, developing such attacks ...

Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care

The integration of artificial intelligence [AI] into clinical trials has revolutionized the process of drug development and personalized medicine. A...

Quantum Threat in Healthcare IoT: Challenges and Mitigation Strategies

The Internet of Things (IoT) has transformed healthcare, facilitating remote patient monitoring, enhanced medication adherence, and chronic disease ...

Privacy-Preserving in Medical Image Analysis: A Review of Methods and Applications

With the rapid advancement of artificial intelligence and deep learning, medical image analysis has become a critical tool in modern healthcare, sig...

Designing DNNs for a trade-off between robustness and processing performance in embedded devices

Machine learning-based embedded systems employed in safety-critical applications such as aerospace and autonomous driving need to be robust against ...

Assessing Foundation Models' Transferability to Physiological Signals in Precision Medicine

The success of precision medicine requires computational models that can effectively process and interpret diverse physiological signals across hete...

Assessing diagnostic performance for common skin diseases using an AI-assisted tele-expertise platform: a proof of concept.

Advancements in machine learning (ML) are making artificial intelligence more feasible in dermatology, with promising results for diagnosing skin canc...

Dec 1 2024 39912464
Primary care research on hypertension: A bibliometric analysis using machine-learning.

Hypertension is one of the most important chronic diseases worldwide. Hypertension is a critical condition encountered frequently in daily life, formi...

Nov 22 2024 39809211
Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.

There is growing excitement about the clinical use of artificial intelligence and machine learning (ML) technologies. Advancements in computing and th...

Nov 15 2024 38995050
Balancing Power and Ethics: A Framework for Addressing Human Rights Concerns in Military AI

AI has made significant strides recently, leading to various applications in both civilian and military sectors. The military sees AI as a solution ...

Advancing Biomedical Signal Security: Real-Time ECG Monitoring with Chaotic Encryption

The real time analysis and secure transmission of electrocardiogram (ECG) signals are critical for ensuring both effective medical diagnosis and pat...

On the Impact of White-box Deployment Strategies for Edge AI on Latency and Model Performance

To help MLOps engineers decide which operator to use in which deployment scenario, this study aims to empirically assess the accuracy vs latency tra...

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