AIMC Topic: Adult

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Health Care Professionals and Data Scientists' Perspectives on a Machine Learning System to Anticipate and Manage the Risk of Decompensation From Patients With Heart Failure: Qualitative Interview Study.

Journal of medical Internet research
BACKGROUND: Heart failure (HF) is a significant global health problem, affecting approximately 64.34 million people worldwide. The worsening of HF, also known as HF decompensation, is a major factor behind hospitalizations, contributing to substantia...

Negative prognostic factors and clinical improvement prediction modeling for extracorporeal shockwave therapy in calcific shoulder tendinitis using artificial intelligence techniques.

Journal of shoulder and elbow surgery
BACKGROUND: The efficacy of extracorporeal shockwave therapy (ESWT) for treating shoulder calcific tendinitis can be influenced by various prognostic factors. This study aimed to identify prognostic factors associated with the failure of ESWT for sym...

Current Practices and Perspectives of Artificial Intelligence in the Clinical Management of Eating Disorders: Insights From Clinicians and Community Participants.

The International journal of eating disorders
OBJECTIVE: Artificial intelligence (AI) could revolutionize the delivery of mental health care, helping to streamline clinician workflows and assist with diagnostic and treatment decisions. Yet, before AI can be integrated into practice, it is necess...

An android can show the facial expressions of complex emotions.

Scientific reports
Trust and rapport are essential abilities for human-robot interaction. Producing emotional expressions in the robots' faces is an effective way for that purpose. Androids can show human-like facial expressions of basic emotions. However, whether andr...

Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.

Neuroradiology
INTRODUCTION: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI a...

AI-generated cancer prevention influencers can target risk groups on social media at low cost.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: This study explores the potential of Artificial Intelligence (AI)-generated social media influencers to disseminate cancer prevention messages. Utilizing a Generative AI (GenAI) application, we created a virtual persona, "Wanda", to promo...

AI-based assessment of longitudinal multiple sclerosis MRI: Strengths and weaknesses in clinical practice.

European journal of radiology
OBJECTIVES: In Multiple Sclerosis (MS) cerebral MRI is essential for disease and treatment monitoring. For this purpose, software solutions are available to support the radiologist with image interpretation and reporting of follow up imaging. Aim of ...

Advancements in Frank's sign Identification using deep learning on 3D brain MRI.

Scientific reports
Frank's sign (FS) is a diagnostic marker associated with aging and various health conditions. Despite its clinical significance, there lacks a standardized method for its identification. This study aimed to develop a deep learning model for automated...

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.

BMC medical imaging
OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to predict pathological grading in pancreatic neuroendocrine tumors (PNETs).

Incremental accumulation of linguistic context in artificial and biological neural networks.

Nature communications
Large Language Models (LLMs) have shown success in predicting neural signals associated with narrative processing, but their approach to integrating context over large timescales differs fundamentally from that of the human brain. In this study, we s...