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HealthEvidence-backed gain

Multiclass Diagnostic Improvement of Interstitial Cystitis (IC) and Overactive Bladder (OAB) via Machine Learning Pipeline on Surface-Enhanced Raman Spectroscopy (SERS)

Interstitial cystitis (IC) and overactive bladder (OAB) are chronic pelvic conditions with shared symptoms of urinary urgency, increased frequency, and nocturia with pain in the bladder. IC is characterized by bladder pain and inflammation without a clear etiology, whereas OAB involves detrusor overactivity in the absence of infection. Despite this symptomatic overlap, IC and OAB differ in underlying pathophysiology and require distinct treatment and medical care. A specific diagnostic strategy is currently lack…

ACS Sensors

Evidence-backed problem

Pope Leo comes out against AI-generated art and calls for an alliance with artists

Evidence-backed problem

Vatican renewing alliance with 'artists and cultural institutions' against AI

Evidence-backed problem

OpenAI disclose another hack on government department in Australia

Evidence-backed gain

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

INTRODUCTION: Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI's role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools. RESEARCH SIGNIFICANCE: This review art…

Both readings

Generative AI and the Information Society: Ethical Reflections from Libraries

The integration of generative artificial intelligence (generative AI) into library systems is transforming the global information society, offering new possibilities for improving information access, management, and dissemination. However, these advancements also raise significant ethical concerns, including algorithmic bias, epistemic injustice, intellectual property conflicts, data privacy breaches, job displacement, the spread of misinformation, and increasing digital inequality. This review critically examin…

Evidence-backed gain

Beyond replacement: human-machine collaboration in the age of AI

Purpose The purpose is to advance the understanding of human-machine (H-M) collaboration in service industries, conceptualizing a framework that structures the research space and proposing a research agenda to guide future studies on optimizing collaboration dynamics, outcomes and ethical governance. Design/methodology/approach The authors use an artificial intelligence (AI)-based systematic literature based on the SERVSIG Literature Alert database to identify articles related to H-M collaboration. Insights from…

Both readings

From Rhizosphere to Resistance: Microbe-Plant Interactions in Eco-Smart Biocontrol

The increasing limitations of chemical pesticides such as environmental pollution, pathogen resistance, and threats to human and ecosystem health have increased the demand for sustainable, biologically based crop protection methods. Eco-smart biocontrol has emerged as a game-changing paradigm that uses beneficial microorganisms associated with plants to suppress phytopathogens, boost plant immunity, and make agroecosystems more resilient over time. Moving beyond traditional single-strain biocontrol, eco-smart bi…

Health

Artificial Intelligence in Mental Health Care: Implications for Psychiatric Mental Health Nursing-A Scoping Review

AI is increasingly being integrated into mental health support, with applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. Although these technologies have demonstrated potential to improve access to care and support clinical practice, their implications for psychiatric mental health nursing (PMHN) remain insufficiently synthesized. This scoping review aimed to examine how AI is being applied in mental health care and to synthesize its implications for…

Health

Melanoma Prognostication Using AI-Guided Histopathology

Accurate diagnosis and risk stratification are central for optimal management of patients with melanoma. Current American Joint Committee on Cancer (AJCC) staging systems inadequately stratify patients with clinically meaningful metastatic potential. Manual histopathologic interpretation compounds this limitation, particularly for diagnostically ambiguous lesions at the benign-malignant interface, where concordance is highly variable. This review examines how computational pathology and convolutional neural netw…

Health

Artificial Intelligence Across the Pharmaceutical Life Cycle: Implications for Industry-Based Clinical Pharmacists

Artificial intelligence (AI) is increasingly shaping the pharmaceutical industry. This ACCP commentary examines the implications of AI for industry-based clinical pharmacists across the pharmaceutical life cycle, including drug development, regulatory affairs, medical affairs, health economics and outcomes research, and pharmacovigilance. Artificial intelligence-enabled tools may support target identification, clinical trial design, regulatory intelligence, evidence synthesis, medical content generation, real-wo…

Health

Integrative Single-Cell Transcriptomics, Multi-Omics Analyses, and Computational Pharmacology Reveal Macrophage Heterogeneity and the Putative THBS1-CD36 Axis in Coronary Atherosclerosis

Coronary atherosclerosis (CA) is characterized by profound macrophage heterogeneity that drives plaque progression and vulnerability, yet the precise subpopulations and their niche-specific functions remain incompletely defined. Here, we constructed a single-cell transcriptomic atlas of human CA using dataset GSE131778 and identified six distinct macrophage subpopulations. Among these, the THBS1+ macrophage subset emerged as a terminally differentiated, hypoxia-adaptive population with elevated TGF-β signaling a…

Health

A review on diffusion tensor imaging-based comprehensive intelligent diagnosis of Alzheimer's disease

AI-assisted early diagnosis of Alzheimer's disease (AD) has substantial clinical value, and diffusion tensor imaging (DTI), which captures white matter microstructural alterations, has considerable potential across the AD continuum. However, major barriers to clinical translation remain. This review systematically evaluated the evolution of algorithmic paradigms, the effectiveness of multimodal fusion, and barriers to clinical generalization in DTI-based AD diagnosis. Using an "Input-Model-Fusion" evaluation fra…

Health

Development and validation of VentPilot: an AI-based recommendation system for mechanical ventilation

Background Mechanical ventilation requires repeated adjustment to changing patient physiology, but consistent individualized management remains challenging. We developed VentPilot, an artificial intelligence-based system for recommending ventilator settings, and evaluated it in multicenter retrospective validation cohorts. Methods VentPilot was developed using offline reinforcement learning on high-resolution physiologic and ventilator trajectories from Seoul National University Hospital (SNUH), with a reward co…

Science

Predicting Hormesis Effects of GenX in Zebrafish via Interpretable Machine Learning: Insights From SHAP Analysis

Hexafluoropropylene oxide-dimer acid (GenX), a prominent alternative to legacy per- and polyfluoroalkyl substances (PFAS), poses a significant challenge to traditional linear risk assessment models due to its ability to induce hormesis-a biphasic "low-dose stimulation, high-dose inhibition" response. This study established an interpretable machine learning (ML) framework to identify and predict GenX-induced non-monotonic dose-response (NMDR) relationships in zebrafish (Danio rerio). By integrating 263 independen…