AIMC Topic: Humans

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Comparison of deep learning-based image segmentation methods for intravascular ultrasound on retrospective and large image cohort study.

Biomedical engineering online
OBJECTIVES: The aim of this study was to investigate the generalization performance of deep learning segmentation models on a large cohort intravascular ultrasound (IVUS) image dataset over the lumen and external elastic membrane (EEM), and to assess...

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability.

BMC medical informatics and decision making
BACKGROUND: Intelligent cardiotocography (CTG) classification can assist obstetricians in evaluating fetal health. However, high classification performance is often achieved by complex machine learning (ML)-based models, which causes interpretability...

Deep learning model for measuring the sagittal Cobb angle on cervical spine computed tomography.

BMC medical imaging
PURPOSES: To develop a deep learning (DL) model to measure the sagittal Cobb angle of the cervical spine on computed tomography (CT).

Machine learning-based approaches for ubiquitination site prediction in human proteins.

BMC bioinformatics
Protein ubiquitination is a critical post-translational modification (PTMs) involved in numerous cellular processes. Identifying ubiquitination sites (Ubi-sites) on proteins offers valuable insights into their function and regulatory mechanisms. Due ...

Label-free identification of protein aggregates using deep learning.

Nature communications
Protein misfolding and aggregation play central roles in the pathogenesis of various neurodegenerative diseases (NDDs), including Huntington's disease, which is caused by a genetic mutation in exon 1 of the Huntingtin protein (Httex1). The fluorescen...

Security Implications of AI Chatbots in Health Care.

Journal of medical Internet research
Artificial intelligence (AI) chatbots like ChatGPT and Google Bard are computer programs that use AI and natural language processing to understand customer questions and generate natural, fluid, dialogue-like responses to their inputs. ChatGPT, an AI...

verified anatomically aware deep learning for real-time electric field simulation.

Journal of neural engineering
Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it en...

MAG-Res2Net: a novel deep learning network for human activity recognition.

Physiological measurement
Human activity recognition (HAR) has become increasingly important in healthcare, sports, and fitness domains due to its wide range of applications. However, existing deep learning based HAR methods often overlook the challenges posed by the diversit...

Artificial intelligence in breast imaging: potentials and challenges.

Physics in medicine and biology
Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, including neoadjuvant chemotherapy, surgery, postoperative chemotherapy, targeted therapy, endocrine ...

Sample size in quantitative instrument-based studies published in Scopus up to 2022: An artificial intelligence aided systematic review.

Acta psychologica
Despite their popularity, quantitative instruments like Likert scales struggle with a practical issue for research projects - how many participants have to fill out the instrument? This study started with the data for 31,271 articles downloaded from ...