AIMC Topic: Adult

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AI in clinical decision-making: ChatGPT-4 vs. Llama2 for otolaryngology cases.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: To evaluate the diagnostic accuracy, appropriateness of additional examination recommendations, and consistency of therapeutic regimens by ChatGPT-4 and Llama2 based on real otolaryngology cases.

Humanoid interfaces in artificial intelligence-based language learning devices: Possible 'Uncanny Valley' effects?

Acta psychologica
The integration of artificial intelligence (AI) into educational tools is transforming learning environments by enabling personalized experiences. This study explores the effectiveness of AI-based educational interfaces, comparing humanoid avatar tut...

Accuracy of robot and template systems in implant cases: A retrospective non-randomized controlled study.

Journal of dentistry
OBJECTIVES: This clinical study aimed to compare the accuracy of implant placement obtained using a robotic system and a full-guide template in patients with dentition defects.

A computed tomography-based deep learning radiomics model for predicting the gender-age-physiology stage of patients with connective tissue disease-associated interstitial lung disease.

Computers in biology and medicine
OBJECTIVES: To explore the feasibility of using a diagnostic model constructed with deep learning-radiomics (DLR) features extracted from chest computed tomography (CT) images to predict the gender-age-physiology (GAP) stage of patients with connecti...

A novel deep neural network approach to detect and monitor cocaine drug abuse.

Computers in biology and medicine
PURPOSE: Cocaine is one of the most commonly used drugs that may lead to physical and mental health problems. It is necessary to identify individuals having cocaine use disorder as early as possible to monitor them properly. The objective of this wor...

Automatic implicit motive codings are at least as accurate as humans' and 99% faster.

Journal of personality and social psychology
Implicit motives, nonconscious needs that influence individuals' behaviors and shape their emotions, have been part of personality research for nearly a century but differ from personality traits. The implicit motive assessment is very resource-inten...

Automating the Addiction Behaviors Checklist for Problematic Opioid Use Identification.

JAMA psychiatry
IMPORTANCE: Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Electronic health records (EHR) allow large-scale studies to identify a continuum of problematic opioid use, including opioid us...

Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System.

JAMA psychiatry
IMPORTANCE: Clinical practice guidelines recommend suicide risk screening and assessment across behavioral health settings. The predictive accuracy of real-world clinician assessments for stratifying patients by risk of future suicidal behavior, howe...

Linking Symptom Inventories Using Semantic Textual Similarity.

Journal of neurotrauma
An extensive library of symptom inventories has been developed over time to measure clinical symptoms of traumatic brain injury (TBI), but this variety has led to several long-standing issues. Most notably, results drawn from different settings and s...

Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.

Hearing research
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from the National Health and Nutritional Examination Survey (NHANES) to develop an interpretable predict...