AIMC Topic: Middle Aged

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Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.

Human brain mapping
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that pr...

Point-of-Care Potassium Measurement vs Artificial Intelligence-Enabled Electrocardiography for Hyperkalemia Detection.

American journal of critical care : an official publication, American Association of Critical-Care Nurses
BACKGROUND: Hyperkalemia can be detected by point-of-care (POC) blood testing and by artificial intelligence- enabled electrocardiography (ECG). These 2 methods of detecting hyperkalemia have not been compared.

Use of Machine Learning Models to Predict Microaspiration Measured by Tracheal Pepsin A.

American journal of critical care : an official publication, American Association of Critical-Care Nurses
BACKGROUND: Enteral feeding intolerance, a common type of gastrointestinal dysfunction leading to underfeeding, is associated with increased mortality. Tracheal pepsin A, an indicator of microaspiration, was found in 39% of patients within 24 hours o...

Artificial Intelligence Models Could Enhance the Diagnostic Accuracy (DA) of Fecal Immunochemical Test (FIT) in the Detection of Colorectal Adenoma in a Screening Setting.

Anticancer research
BACKGROUND/AIM: This study evaluated the diagnostic accuracy (DA) for colorectal adenomas (CRA), screened by fecal immunochemical test (FIT), using five artificial intelligence (AI) models: logistic regression (LR), support vector machine (SVM), neur...

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning.

Brain and behavior
PURPOSE: The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magn...

Deep Learning-Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach.

Brain and behavior
PURPOSE: A debilitating and poorly understood symptom of Parkinson's disease (PD) is freezing of gait (FoG), which increases the risk of falling. Clinical evaluations of FoG, relying on patients' subjective reports and manual examinations by speciali...

World-making for a future with sentient AI.

The British journal of social psychology
The ways people imagine possible futures with artificial intelligence (AI) affects future world-making-how the future is produced through cultural propagation, design, engineering, policy, and social interaction-yet there has been little empirical st...

Nostalgia encourages exploration and fosters uncertainty in response to AI technology.

The British journal of social psychology
The burgeoning progress of cutting-edge technology paradoxically evokes nostalgia. How does this emotion influence responses to innovative technology, such as Artificial Intelligence (AI)? We hypothesized that two pathways operate concurrently. First...

Investigating the Differential Impact of Psychosocial Factors by Patient Characteristics and Demographics on Veteran Suicide Risk Through Machine Learning Extraction of Cross-Modal Interactions.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Accurate prediction of suicide risk is crucial for identifying patients with elevated risk burden, helping ensure these patients receive targeted care. The US Department of Veteran Affairs' suicide prediction model primarily leverages structured elec...

Evaluation of temporomandibular joint disc displacement with MRI-based radiomics analysis.

Dento maxillo facial radiology
OBJECTIVES: The purpose of this study was to propose a machine learning model and assess its ability to classify temporomandibular joint (TMJ) disc displacements on MR T1-weighted and proton density-weighted images.