Cultural Competence

Artificial intelligence-predicted ECG age gap as a biomarker: bias-adjusted correlation with mortality and cardiovascular risk factors.

AIMS: Artificial intelligence models can estimate a person's age from ECG. The gap between the predicted ECG age and chronological age, predicted age deviation (PAD), has been associated with cardiovascular risk factors and mortality. However, regression bias causes PAD to correlate with chronological age itself, potentially distorting these associations. OBJECTIVES: To investigate the bias introd...

Linking speech patterns to brain structure in affective and psychotic disorders: an integrative natural language processing approach.

Language disturbances are central features of serious mental illnesses, yet traditional clinical assessments often rely on subjective evaluation that may overlook subtle speech anomalies. This study employs natural language processing (NLP) to objectively analyze spontaneous speech in a transdiagnostic sample comprising individuals with affective (n = 119 Major Depressive Disorder, n = 27 Bipolar ...

Consensus-guided individual graph learning via enhanced tensor low-rank for robust multi-view clustering.

Most graph-based multi-view clustering methods first learn individual similarity graphs for each view and then derive a consensus graph from these sim...

Early identification of pediatric depression in western China: A multicenter, citywide evaluation of nine machine learning models.

BACKGROUND: Childhood depression is an emerging global concern, yet knowledge and early detection tools remain limited in low- and middle-income regio...

Streamlining the Histopathologic Workflow in Diabetic Kidney Disease with Artificial Intelligence.

KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models and reduced translational gaps when applied to hum...

Balancing Innovation and Humanism: An Ethical Debate on AI and VR in Psychiatric Nursing Education.

BACKGROUND: Artificial intelligence (AI) and virtual reality (VR) technologies are increasingly integrated into psychiatric nursing education, present...

Artificial Intelligence Use in Acne Diagnosis and Management-A Scoping Review.

Artificial intelligence (AI) techniques can allow for early diagnosis and treatment of acne. Bias in AI model training remains, leading to various cha...

Acoustic and machine learning methods for speech-based suicide risk assessment: A systematic review.

Suicide remains a public health challenge, necessitating improved detection methods to facilitate timely intervention and treatment. This systematic r...

Enhancing Cultural Competence in Nursing Education Through Generative Artificial Intelligence Tools.

INTRODUCTION: Cultural competence is vital for nursing students providing patient-centered care. Generative artificial intelligence (AI) tools can enh...

Balancing Bias and Variance in Deep Learning-Based Tumor Microstructural Parameter Mapping.

PURPOSE: Time-dependent diffusion MRI enables quantification of tumor microstructural parameters useful for diagnosis and prognosis. Nevertheless, cur...

Comparative analysis of human-generated versus Artificial Intelligence-drafted summary paragraphs for medical student performance evaluations.

PURPOSE: This study evaluated the efficiency and effectiveness of using Generative Artificial Intelligence (GenAI) to draft Medical Student Performanc...

FAST: Foreground-aware active self-training for domain adaptive object detection.

Domain adaptive object detection (DAOD) aims to enable object detectors to perform well on an unlabeled target domain that differs from the source dom...

Fine-tuning large language models in federated learning with fairness-aware prompt selection.

Large language models (LLMs) require domain-specific fine-tuning for real-world deployment, yet face critical barriers of data privacy and computation...

Disability portrayals in artificial intelligence text-to-image generation: Influence of context and the medicalization of disability.

PURPOSE/OBJECTIVE: Text-to-image (TTI) systems are artificial intelligence (AI) models that incorporate large amounts of data to produce high-resoluti...

Liquid biopsy based on multi-targeted capture of urinary tumor DNA combined with machine learning to detect urothelial carcinoma: a multicenter prospective study.

PURPOSE: Diagnostics for urothelial carcinoma have low sensitivity, thereby negatively impacting diagnostic outcomes. Herein, we present BiovueUro, a ...

Generating Brain MRI with StyleGAN2-ADA: The Effect of the Training Set Size on the Quality of Synthetic Images.

The potential of deep learning for medical imaging is often constrained by limited data availability. Generative models can unlock this potential by g...

Recent biotechnological advances in bioprospecting secondary metabolites from endolichenic fungi for drug discovery applications.

Endolichenic fungi (ELF) are symbiotic organisms residing in lichens. Since the initial report of its application in natural products and drug discove...

Artificial intelligence in gastric cancer: a systematic review of machine learning and deep learning applications.

BACKGROUND: Gastric cancer (GC) remains a major global health concern, ranking as the fifth most prevalent malignancy and the fourth leading cause of ...

Edge-Centric Brain Connectome Representations Reveal Increased Brain Functional Diversity of Reward Circuit in Patients With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) has been increasingly understood as a disorder of network-level functional dysconnectivity. However, previ...

Tailoring knowledge for empowered cooperative actions in multi-agent reinforcement learning.

Behavioral diversity emerges as a crucial factor for achieving effective collaboration in Multi-Agent Reinforcement Learning (MARL). Current methods o...