Artificial Intelligence Medical Compendium

OBJECTIVE: The aim of this study was to evaluate the performance of a deep learning (DL) model in automatically identifying dental trauma types on selected periapical radiographs, classified according to the Andreasen system. METHODS AND MATERIALS: S... read more 

OBJECTIVE: To evaluate the diagnostic accuracy and workflow efficiency of BioticsAI-anatomyUNet-0.1-2022 software in identifying 18 standard fetal anatomical planes during mid-trimester ultrasound, and to assess the influence of maternal body mass in... read more 

PURPOSE: This study aims to evaluate whether quantitative imaging features analyzed by an artificial intelligence (AI) tool are associated with success rate, histopathological results, and complication risks of CT-guided lung biopsies. METHODS: A ret... read more 

Artificial intelligence (AI) can transform mental health care globally by improving the efficiency, consistency, effectiveness and accessibility of training and supervision in evidence-based psychotherapies, including cognitive and behavioral therapi... read more 

PURPOSE: Recent advances in multimodal large language models (LLMs) have demonstrated promising potential for medical image analysis, yet their diagnostic capability in thyroid ultrasound remains unverified. This study explored the feasibility of Cha... read more 

Triple negative breast cancer (TNBC) is the most malignant subtype of breast cancer (BC), which accounts for 10-20 % of BC incidences, and its early diagnosis is pivotal to curing the disease. Tissue biopsies, surgical biopsies, and needle biopsies, ... read more 

We developed neural network models trained with images from Klebsiella pneumoniae genomes, encoded via Chaos Game Representation, to predict carbapenem resistance. Both real (n = 168) and synthetic AI-generated (n = 200) images were used. The best-pe... read more 

INTRODUCTION AND AIMS: Clinical fractures remain the primary cause of failure in dental all-ceramic restorations, highlighting the need to improve the mechanical performance and durability of ceramic material. This study aimed to develop a large lang... read more 

BACKGROUND: Oral lichen planus (OLP), oral lichenoid lesions (OLL), and squamous cell carcinoma on a lichenoid background (SCC-over-LP/LLP) overlap clinically, delaying malignant transformation recognition. OBJECTIVE: To evaluate a multimodal large l... read more 

BACKGROUND: Cognitive impairment in older adults poses a growing public health challenge, yet accessible screening tools remain limited. We aimed to develop and validate an interpretable machine learning model for cognitive impairment prediction by r... read more