AIMC Topic: Humans

Clear Filters Showing 4721 to 4730 of 95995 articles

The need for guardrails with large language models in pharmacovigilance and other medical safety critical settings.

Scientific reports
Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the issue of "hal...

Deep learning-based real-time detection of head and neck tumors during radiation therapy.

Physics in medicine and biology
Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are accounting for motion caused by changes to the immobilization mask fit, and to reduce mask-related patient distress by replacing the masks with patien...

Structural modification strategies for ferritin nanoparticles and their applications in biomedicine: a narrative review.

Nanoscale
Ferritin is an iron-storage protein that naturally self-assembles into a hollow spherical particle consisting of 24 identical subunits, and it serves a central role in iron metabolism. Ferritin's favorable drug-loading capacity, biocompatibility, int...

A hybrid supervised and unsupervised machine learning approach for identifying nucleoside drugs using nanopore readouts.

Nanoscale
Nucleoside drugs, mimics of natural nucleosides, have become cornerstone treatments in clinical approaches to combat cancer and viral infections. The analysis of nucleoside drugs is commonly performed using liquid chromatography-tandem mass spectrome...

AI-Driven fetal distress monitoring SDN-IoMT networks.

PloS one
The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT) with AI-powered networks for improved clinical connectivity and advanced monitoring capabilities. However, IoMT devices struggle with traditional ne...

A bearing fault diagnosis method based on hybrid artificial intelligence models.

PloS one
The working state of rolling bearing severely affects the performance of industrial equipment. Addressing the issue of that the difficulty of incipient weak signals feature extraction influences the rolling bearing diagnosis accuracy, an efficient be...

Uncovering locomotor learning dynamics in people with Parkinson's disease.

PloS one
Locomotor learning is important for improving gait and balance impairments in people with Parkinson's disease (PD). While PD disrupts neural networks involved in motor learning, there is a limited understanding of how PD influences the time course of...

Decoding corporate communication strategies: Analysing mandatory published information under Pillar 3 across turbulent periods with unsupervised machine learning.

PloS one
This study explores the communication patterns of Slovak banks with stakeholders through mandatory disclosures mandated by Basel III's Pillar 3 framework and annual reports in 2007-2022. Our primary objective is to identify key topics communicated by...

Predicting adolescent suicide risk using integrated data from adolescents, parents and siblings: An analysis of multiple machine learning models.

Journal of affective disorders
Adolescent suicide is a critical public health issue, yet accurately predicting suicide risk remains challenging. Few studies integrate adolescents' self-reports with mental health, especially suicidality assessments from parents and siblings. This s...

Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis.

Human vaccines & immunotherapeutics
Exploring the influencing factors of COVID-19 vaccine hesitancy and summarizing countermeasures is of great significance for effectively addressing potential public health crises. Based on survey data from China, we employed a Gradient Boosting Decis...