AIMC Topic: Humans

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SMOTE-Enhanced Explainable Artificial Intelligence Model for Predicting Visual Field Progression in Myopic Normal Tension Glaucoma.

Journal of glaucoma
PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension glaucoma. Using SHAP analysis, the key variables driving disease progression were identified.

Advancing lung transplantation through machine learning and artificial intelligence.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: To explore the current applications of artificial intelligence and machine learning in lung transplantation, including outcome prediction, drug dosing, and the potential future uses and risks as the technology continues to evolve.

Artificial Intelligence-Enabled Quantitative Assessment and Intervention for Heart Inflammation Model Organoids.

Angewandte Chemie (International ed. in English)
Inflammation plays a crucial role in progression of cardiovascular diseases (CVDs); thus, the discovery of rapid and precise analytical tools to assess inflammation related to CVDs is highly desirable for their diagnosis and therapeutic discovery. Ho...

PLGA-based long-acting injectable (LAI) formulations.

Journal of controlled release : official journal of the Controlled Release Society
Long-acting injectable (LAI) formulations, which deliver drugs over weeks or months, have been in use for more than three decades. Most clinically approved LAI products are formulated using poly(lactide-co-glycolide) (PLGA) polymers. Historically, th...

OrgaMeas: A pipeline that integrates all the processes of organelle image analysis.

Biochimica et biophysica acta. Molecular cell research
Although image analysis has emerged as a key technology in the study of organelle dynamics, the commonly used image-processing methods, such as threshold-based segmentation and manual setting of regions of interests (ROIs), are error-prone and labori...

Initial seizure episodes risk factors identification during hospitalization of ICU patients: A retrospective analysis of the eICU collaborative research database.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: We aimed to identify risk factors for initial seizure episodes in ICU patients using various machine learning algorithms.

An artificial intelligence perspective on geriatric syndromes: assessing the information accuracy and readability of ChatGPT.

European geriatric medicine
PURPOSE: ChatGPT, a comprehensive language processing model, provides the opportunity for supportive and professional interactions with patients. However, its use to address patients' frequently asked questions (FAQs) and the readability of the text ...

Early operative difficulty assessment in laparoscopic cholecystectomy via snapshot-centric video analysis.

International journal of computer assisted radiology and surgery
PURPOSE: Laparoscopic cholecystectomy (LC) operative difficulty (LCOD) is highly variable and influences outcomes. Despite extensive LC studies in surgical workflow analysis, limited efforts explore LCOD using intraoperative video data. Early recogni...

Towards real-time conformal palliative treatment of spine metastases: A deep learning approach for Hounsfield Unit recovery of cone beam CT images.

Medical physics
BACKGROUND: The extension of onboard cone-beam CT (CBCT) imaging for real-time treatment planning is constrained by limitations in image quality. Synthetic CT (sCT) generation using deep learning provides a potential solution to these limitations.

A CVAE-based generative model for generalized B inhomogeneity corrected chemical exchange saturation transfer MRI at 5 T.

NeuroImage
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful tool to image endogenous or exogenous macromolecules. CEST contrast highly depends on radiofrequency irradiation B level. Spatial inhomogeneity of...