AIMC Topic: Artificial Intelligence

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Prediction of postoperative intensive care unit admission with artificial intelligence models in non-small cell lung carcinoma.

European journal of medical research
BACKGROUND: There is no standard practice for intensive care admission after non-small cell lung cancer surgery. In this study, we aimed to determine the need for intensive care admission after non-small cell lung cancer surgery with deep learning mo...

Artificial intelligence performance in answering multiple-choice oral pathology questions: a comparative analysis.

BMC oral health
BACKGROUND: Artificial intelligence (AI) has rapidly advanced in healthcare and dental education, significantly impacting diagnostic processes, treatment planning, and academic training. The aim of this study is to evaluate the performance difference...

Performance of artificial intelligence chatbots in responding to the frequently asked questions of patients regarding dental prostheses.

BMC oral health
BACKGROUND: Artificial intelligence (AI) chatbots are increasingly used in healthcare to address patient questions by providing personalized responses. Evaluating their performance is essential to ensure their reliability. This study aimed to assess ...

Artificial intelligence utilization in cancer screening program across ASEAN: a scoping review.

BMC cancer
BACKGROUND: Cancer remains a significant health challenge in the ASEAN region, highlighting the need for effective screening programs. However, approaches, target demographics, and intervals vary across ASEAN member states, necessitating a comprehens...

Leveraging artificial intelligence in the prediction, diagnosis and treatment of depression and anxiety among perinatal women in low- and middle-income countries: a systematic review.

BMJ mental health
AIM: The adoption of artificial intelligence (AI) tools is gaining traction in maternal mental health (MMH) research. Despite its growing usage, little is known about its prospects and challenges in low- and middle-income countries (LMICs). This stud...

Detection of diabetic macular oedema patterns with fine-grained image categorisation on optical coherence tomography.

BMJ open ophthalmology
PURPOSE: To develop an artificial intelligence (AI) system for detecting pathological patterns of diabetic macular oedema (DME) with fine-grained image categorisation using optical coherence tomography (OCT) images.

Barriers to and facilitators of clinician acceptance and use of artificial intelligence in healthcare settings: a scoping review.

BMJ open
OBJECTIVES: This study aimed to systematically map the evidence and identify patterns of barriers and facilitators to clinician artificial intelligence (AI) acceptance and use across the types of AI healthcare application and levels of income of geog...

Ethical implications related to processing of personal data and artificial intelligence in humanitarian crises: a scoping review.

BMC medical ethics
BACKGROUND: Humanitarian organizations are rapidly expanding their use of data in the pursuit of operational gains in effectiveness and efficiency. Ethical risks, particularly from artificial intelligence (AI) data processing, are increasingly recogn...

Generative AI in Otolaryngology Residency Personal Statement Writing: A Mixed-Methods Analysis.

The Laryngoscope
OBJECTIVE: Generative Artificial Intelligence (GAI) interfaces have rapidly integrated into various societal domains. Widespread accessibility of GAI for drafting personal statements poses challenges for evaluators to gauge writing ability and person...

AI as teacher: effectiveness of an AI-based training module to improve trainee pediatric fracture detection.

Skeletal radiology
OBJECTIVE: Prior work has demonstrated that AI access can help residents more accurately detect pediatric fractures. We wished to evaluate the effectiveness of an unsupervised AI-based training module as a pediatric fracture detection educational too...