AIMC Topic: Humans

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Deep-learning-based motion correction using multichannel MRI data: a study using simulated artifacts in the fastMRI dataset.

NMR in biomedicine
Deep learning presents a generalizable solution for motion correction requiring no pulse sequence modifications or additional hardware, but previous networks have all been applied to coil-combined data. Multichannel MRI data provide a degree of spati...

Does machine learning have a high performance to predict obesity among adults and older adults? A systematic review and meta-analysis.

Nutrition, metabolism, and cardiovascular diseases : NMCD
AIM: Machine learning may be a tool with the potential for obesity prediction. This study aims to review the literature on the performance of machine learning models in predicting obesity and to quantify the pooled results through a meta-analysis.

Identification of Root Canal Morphology in Fused-rooted Mandibular Second Molars From X-ray Images Based on Deep Learning.

Journal of endodontics
INTRODUCTION: Understanding the intricate anatomical morphology of fused-rooted mandibular second molars (MSMs) is essential for root canal treatment. The present study utilized a deep learning approach to identify the three-dimensional root canal mo...

Progress of Artificial Intelligence-Driven Solutions for Automated Segmentation of Dental Pulp Space on Cone-Beam Computed Tomography Images. A Systematic Review.

Journal of endodontics
INTRODUCTION: Automated segmentation of 3-dimensional pulp space on cone-beam computed tomography images presents a significant opportunity for enhancing diagnosis, treatment planning, and clinical education in endodontics. The aim of this systematic...

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion.

Biotechnology and bioengineering
Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their ...

Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing both the intratumoral and peritumoral-to predict the status of axillary lymph nodes in patients with...

Fillable Magnetic Microrobots for Drug Delivery to Cardiac Tissues In Vitro.

Advanced healthcare materials
Many cardiac diseases, such as arrhythmia or cardiogenic shock, cause irregular beating patterns that must be regulated to prevent disease progression toward heart failure. Treatments can include invasive surgery or high systemic drug dosages, which ...

Artificial intelligence in maxillofacial and facial plastic and reconstructive surgery.

Current opinion in otolaryngology & head and neck surgery
PURPOSE OF REVIEW: To provide a current review of artificial intelligence and its subtypes in maxillofacial and facial plastic surgery including a discussion of implications and ethical concerns.

UmamiPreDL: Deep learning model for umami taste prediction of peptides using BERT and CNN.

Computational biology and chemistry
Taste is crucial in driving food choice and preference. Umami is one of the basic tastes defined by characteristic deliciousness and mouthfulness that it imparts to foods. Identification of ingredients to enhance umami taste is of significant value t...