Care of terminally ill / Palliative care

Progression without progress.

Progress in the use of artificial intelligence (AI) to advance scientific discovery has made it increasingly realistic to envision automated "end-to-end science" (ETES) systems: integrated pipelines that could generate hypotheses, run experiments (in silico or robotic), analyze results, and produce publishable outputs with minimal human intervention. The critical question is not whether AI can "do...

Art management platform based on virtual scenes.

This article is based on the form of "VR + Art Platform" and designs an art management platform that integrates display, trading, and socializing. The development of front-end work is carried out using Unity 3D engine, and modeling software such as 3ds Max is used to model the models used in the system. The backend is developed using IntelliJ IDEA platform, and the SSM framework is built and combi...

End-user perspectives on the use of personal health information for AI development and the use of AI in care: an interview study.

INTRODUCTION: The rapid advancement of artificial intelligence (AI) in health care necessitates that decision-makers consider end-user views on second...

A non-invasive end-to-end intelligent assistance system for breast ultrasound.

Although artificial intelligence enhances medical image classification to effectively improve lesion diagnosis accuracy and efficiency, it still faces...

Knowledge-prior memory discrimination based generative adversarial network for industrial anomaly detection and localization.

Industrial anomaly detection and localization have become key procedures in modern manufacturing for product quality assurance. However, it is still c...

Empowering precision source apportionment and risk management of microplastics with an optimized fingerprint-receptor model and smart platform.

Accurate source apportionment of sediment microplastics (MPs) is essential for effective ecological risk management. However, conventional receptor mo...

Multimodal Personalized Mobile Health Just-in-Time Adaptive Intervention for Occupational Stress Management: Pilot Study.

BACKGROUND: As digital health solutions gain traction, there is an urgent need for effective, person-centered stress management tools for employees. A...

Temporally rigorous and traceable predictive maintenance via joint labeler-model optimization.

Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to o...

Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.

There is a lack of automated pipelines for diagnostic classification of point-of-care tests for neglected tropical diseases. Here, we present an end-t...

Generative artificial intelligence for inpatient documentation summarization: mixed-methods quality assessment and early real-world experience.

OBJECTIVE: We evaluated the quality and adoption of a large language model (LLM)-based summarization tool for ongoing hospital care. MATERIALS AND MET...

Research on the efficacy of hybrid deep learning models for image-based classification of common oral conditions.

OBJECTIVE: To compare tuned end-to-end and hybrid deep learning strategies for image-based classification of common oral conditions under small and im...

Use of Generative Artificial Intelligence in the Management of Low Back Pain: a Scoping Review.

BACKGROUND CONTEXT: Low back pain (LBP) is common and a major cause of disability globally. Generative artificial intelligence (GenAI) such as ChatGPT...

The Last Mile Problem: A Critical Assessment of Physics-Based and AI Tools for Small Molecule Binding Prediction in Virtual Screening.

Docking-based virtual screening (VS) is essential for hit finding in the initial stage of drug or probe discovery. However, it remains prone to high f...

Input-to-State Safety for Reinforcement Learning.

In this article, we present a novel off-policy, safe reinforcement learning (RL) approach for nonlinear dynamical systems under input saturation that ...

End-of-surgery prediction of postoperative infectious complications from intraoperative vital-sign dynamics.

Infections after surgery remain a leading cause of morbidity and mortality, yet reliable risk stratification at the end of surgery is limited. Intraop...

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale.

OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommen...

Homogeneous image-based digital immunoassays with high error tolerance.

There is a significant global health need to translate more in vitro diagnostic tests from clinical laboratories to field-based applications, includin...

The architecture of computational antiviralism: a multi-scale framework from molecular targeting to viral ecosystem engineering.

The recurrent outbreak of viral pathogens and the possibility of the new pandemics demand the transition to the predictive and integrative computation...

Applicable Scenarios, Desired Features, and Risks of AI Psychotherapists in Depression Treatment From the Patient's Perspective: Exploratory Qualitative Study.

BACKGROUND: Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advance...

Machine Learning Interpretability to Assess the Association Between Time in Tight Range and Mortality in Cardiogenic Shock.

BACKGROUND: Cardiogenic shock (CS) is a critical condition of end-organ hypoperfusion with high mortality. Fluctuations in blood glucose (BG) levels m...