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The levers of political persuasion with conversational artificial intelligence.

Science (New York, N.Y.)
There are widespread fears that conversational artificial intelligence (AI) could soon exert unprecedented influence over human beliefs. In this work, in three large-scale experiments ( = 76,977 participants), we deployed 19 large language models (LL...

An Improved Deep Semi-supervised JNMF Method for Biomarker Extraction of Alzheimer's Disease.

Journal of molecular neuroscience : MN
Imaging genetics is an approach that explores the underlying mechanisms of brain disorders such as Alzheimer's disease (AD) by analyzing the correlation between neuroimaging and genetic data. Traditional non-negative matrix factorization (NMF) algori...

Artificial inteligence reading of cystometric traces provides good correlation with human diagnosis.

World journal of urology
AIM: Urodynamic studies are essential for diagnosing lower urinary tract dysfunction but are expert-dependent and time-consuming. Artificial intelligence (AI), notably machine learning (ML) and deep learning (DL) may help automate and standardize int...

Assessing the Accuracy of Artificial Intelligence in Detecting Intracranial Aneurysms in a Clinical Setting Relative to Neuroradiologists.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Intracranial aneurysms (IAs), detected in 2%-5% of the population, represent a major health care issue because ruptured aneurysms with resultant hemorrhage are associated with severe morbidity or mortality. With the increasing...

An automated classification of brain white matter inherited disorders (Leukodystrophy) using MRI image features.

Biomedical physics & engineering express
Leukodystrophies are a group of inherited disorders that predominantly and selectively affect the white matter of the central nervous system. Their overlapping clinical and imaging manifestations make a timely and accurate diagnosis challenging. In t...

Both Infarcted and Noninfarcted Brain Regions Contribute to Deep Learning-Based MRI Prediction of Acute Stroke Outcome.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different r...

Artificial Intelligence-Driven Detection of Large Vessel Occlusions on NCCT: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Imaging triage of stroke patients is primarily based on perfusion imaging. Simplified triage based on non-contrast CT are limited (NCCT). To evaluate the predictive capability of a deep learning algorithm, "Triage Stroke" (Bra...

Abnormal brain network reconfiguration in neuropsychiatric disorders across cognitive decline, Depression, and Schizophrenia.

PloS one
OBJECTIVE: Neuropsychiatric disorders are characterized by high complexity and comorbidity, imposing a substantial burden on both patients and society. However, their elusive pathogenic mechanisms impede accurate clinical diagnosis and effective inte...

Identification and validation of palmitoylation-related signature genes based on machine learning for prostate cancer.

PloS one
Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men, with challenges in diagnosis and treatment due to tumor heterogeneity. This study identifies palmitoylation-related signature genes as potential diagnostic and therapeu...

Advances in deep reinforcement learning enable better predictions of human behavior in time-continuous tasks.

PloS one
Humans have to respond to everyday tasks with goal-directed actions in complex and time-continuous environments. However, modeling human behavior in such environments has been challenging. Deep Q-networks (DQNs), an application of deep learning used ...