AI Medical Compendium Topic:
Prospective Studies

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Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

European radiology
OBJECTIVES: To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of...

Diagnostic evaluation of deep learning accelerated lumbar spine MRI.

The neuroradiology journal
BACKGROUND AND PURPOSE: Deep learning (DL) accelerated MR techniques have emerged as a promising approach to accelerate routine MR exams. While prior studies explored DL acceleration for specific lumbar MRI sequences, a gap remains in comprehending t...

Assessing prognosis in depression: comparing perspectives of AI models, mental health professionals and the general public.

Family medicine and community health
BACKGROUND: Artificial intelligence (AI) has rapidly permeated various sectors, including healthcare, highlighting its potential to facilitate mental health assessments. This study explores the underexplored domain of AI's role in evaluating prognosi...

The morphokinetic signature of human blastocysts with mosaicism and the clinical outcomes following transfer of embryos with low-level mosaicism.

Journal of ovarian research
BACKGROUND: Genetic mosaicism is commonly observed in human blastocysts. Embryos' morphokinetic feature observed from time-lapse monitoring (TLM) is helpful to predict the embryos' ploidy status in a non-invasive way. However, morphokinetic research ...

Reliability of large language models in managing odontogenic sinusitis clinical scenarios: a preliminary multidisciplinary evaluation.

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: This study aimed to evaluate the utility of large language model (LLM) artificial intelligence tools, Chat Generative Pre-Trained Transformer (ChatGPT) versions 3.5 and 4, in managing complex otolaryngological clinical scenarios, specificall...

Historical perspective and future directions: computational science in immuno-oncology.

Journal for immunotherapy of cancer
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, undersc...

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BMC geriatrics
BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impair...

The buccal micronucleus cytome assay: New horizons for its implementation in human studies.

Mutation research. Genetic toxicology and environmental mutagenesis
In this report we provide a summary of the presentations and discussion of the latest knowledge regarding the buccal micronucleus (MN) cytome assay. This information was presented at the HUMN workshop held in Malaga, Spain, in connection with the 202...

Implementing a deep learning model for automatic tongue tumour segmentation in ex-vivo 3-dimensional ultrasound volumes.

The British journal of oral & maxillofacial surgery
Three-dimensional (3D) ultrasound can assess the margins of resected tongue carcinoma during surgery. Manual segmentation (MS) is time-consuming, labour-intensive, and subject to operator variability. This study aims to investigate use of a 3D deep l...

Evaluating the Reliability of a Remote Acuity Prediction Tool in a Canadian Academic Emergency Department.

Annals of emergency medicine
STUDY OBJECTIVE: There is increasing interest in harnessing artificial intelligence to virtually triage patients seeking care. The objective was to examine the reliability of a virtual machine learning algorithm to remotely predict acuity scores for ...