AIMC Topic: Adult

Clear Filters Showing 3251 to 3260 of 15606 articles

Machine learning analysis of the relationships between traumatic childbirth experience with positive and negative fertility motivations in Iran in a community-based sample.

Reproductive health
BACKGROUND: Psychologically traumatic childbirth leads to short and long-term negative impacts on a woman's health and impacts future reproductive decisions. Considering the importance of fertility growth and strengthening positive fertility motivati...

Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning.

BMC medical informatics and decision making
BACKGROUND: Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and intervention in risk populations...

Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models.

BMC medical informatics and decision making
INTRODUCTION: Renal transplantation is a critical treatment for end-stage renal disease, but graft failure remains a significant concern. Accurate prediction of graft survival is crucial to identify high-risk patients. This study aimed to develop pro...

The impact of action descriptions on attribution of moral responsibility towards robots.

Scientific reports
In the era of renewed fascination with AI and robotics, one needs to address questions related to their societal impact, particularly in terms of moral responsibility and intentionality. In seven vignette-based experiments we investigated whether the...

Feasibility of remote robot empowered teleultrasound scanning for radioactive patients.

Scientific reports
To investigate the feasibility of robot-assisted teleultrasound diagnosis for radioactive patients compared with conventional ultrasound diagnosis. In this prospective study (ChineseClinicalTrials.gov identifier, ChiCTR2200057253), 32 radioactive pat...

Deep learning and radiomics for gastric cancer serosal invasion: automated segmentation and multi-machine learning from two centers.

Journal of cancer research and clinical oncology
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...

AI language model rivals expert ethicist in perceived moral expertise.

Scientific reports
People view AI as possessing expertise across various fields, but the perceived quality of AI-generated moral expertise remains uncertain. Recent work suggests that large language models (LLMs) perform well on tasks designed to assess moral alignment...

Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Scientific reports
Previous deep learning-based brain network research has made significant progress in understanding the pathophysiology of schizophrenia. However, it ignores the three-dimensional spatial characteristics of EEG signals and cannot dynamically learn the...

Applicability of Artificial Intelligence Analysis in Oral Cytopathology: A Pilot Study.

Acta cytologica
INTRODUCTION: Oral cancer, especially oral squamous cell carcinoma (OSCC), is a global health challenge due to factors such as late detection and high mortality rates. Early detection is essential through monitoring by healthcare professionals. Cytop...

Assessment of ChatGPT-generated medical Arabic responses for patients with metabolic dysfunction-associated steatotic liver disease.

PloS one
BACKGROUND AND AIM: Artificial intelligence (AI)-powered chatbots, such as Chat Generative Pretrained Transformer (ChatGPT), have shown promising results in healthcare settings. These tools can help patients obtain real-time responses to queries, ens...