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People are poorly equipped to detect AI-powered voice clones.

Scientific reports
As generative artificial intelligence (AI) continues its ballistic trajectory, everything from text to audio, image, and video generation continues to improve at mimicking human-generated content. Through a series of perceptual studies, we report on ...

Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.

Open heart
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...

Exploring the Capacity of Large Language Models to Assess the Chronic Pain Experience: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Chronic pain, affecting more than 20% of the global population, has an enormous pernicious impact on individuals as well as economic ramifications at both the health and social levels. Accordingly, tools that enhance pain assessment can c...

AI-Based Identification Method for Cervical Transformation Zone Within Digital Colposcopy: Development and Multicenter Validation Study.

JMIR cancer
BACKGROUND: In low- and middle-income countries, cervical cancer remains a leading cause of death and morbidity for women. Early detection and treatment of precancerous lesions are critical in cervical cancer prevention, and colposcopy is a primary d...

Optimizing Initial Vancomycin Dosing in Hospitalized Patients Using Machine Learning Approach for Enhanced Therapeutic Outcomes: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Vancomycin is commonly dosed using standard weight-based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal therapeutic outcomes. A predictive ...

Online Health Information-Seeking in the Era of Large Language Models: Cross-Sectional Web-Based Survey Study.

Journal of medical Internet research
BACKGROUND: As large language model (LLM)-based chatbots such as ChatGPT (OpenAI) grow in popularity, it is essential to understand their role in delivering online health information compared to other resources. These chatbots often generate inaccura...

Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence.

Journal of medical Internet research
BACKGROUND: Noninvasive volumetric measurements during the first trimester of pregnancy provide unique insight into human embryonic growth and development. However, current methods, such as semiautomatic (eg, virtual reality [VR]) or manual segmentat...

Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study.

JMIR aging
BACKGROUND: Alzheimer disease and related dementias (ADRD) exhibit prominent heterogeneity. Identifying clinically meaningful ADRD subtypes is essential for tailoring treatments to specific patient phenotypes.

Using machine learning to identify features associated with different types of self-injurious behaviors in autistic youth.

Psychological medicine
BACKGROUND: Self-injurious behaviors (SIB) are common in autistic people. SIB is mainly studied as a broad category, rather than by specific SIB types. We aimed to determine associations of distinct SIB types with common psychiatric, emotional, medic...

Parallel convolutional neural networks for non-invasive cardiac hemodynamic estimation: integrating uncalibrated PPG signals with nonlinear feature analysis.

Physiological measurement
Understanding cardiac hemodynamic status (CHS) is essential for accurate cardiovascular health assessment, as it is governed by key parameters such as cardiac output (CO), systemic vascular resistance (SVR), and arterial compliance (AC). This study a...