AIMC Topic: Humans

Clear Filters Showing 691 to 700 of 95995 articles

Advancements in the study of exosomes in disease diagnosis and treatment.

International journal of pharmaceutics
Exosomes are small, membrane-enclosed vesicles that can originate from a variety of sources and contain a wealth of material. They are involved in physiological processes such as cell-cell communication, cell migration, and anti-tumor immunity, and a...

Overcoming Challenges in Electrochemical Sensing: Toward Continuous Monitoring.

ACS sensors
The advancement of decentralized and real-time monitoring necessitates robust electrochemical sensors that can operate continuously in complex environments. However, transitioning these sensors from laboratory prototypes to reliable field devices rem...

BioFusionDTI: Assimilating Graph and Sequence Modalities for Generalizable Drug-Target Interaction Prediction.

Journal of chemical information and modeling
Accurate prediction of drug-target interactions (DTIs) is essential for drug discovery and repurposing. Despite recent advances, deep learning models often exhibit limited generalization under realistic cold-start scenarios and suffer from poor inter...

Performance of large language models in non-English medical ethics-related multiple choice questions: comparison of ChatGPT performance across versions and languages.

BMC medical ethics
BACKGROUND: As large language models (LLMs) evolve, assessing their competence in ethically sensitive domains such as medical ethics has become increasingly important. Since medical ethics is a universal component of medical education, disparities in...

A machine learning model for predicting 28-day mortality in ICU patients with community-acquired pneumonia and acute kidney injury.

Scientific reports
Acute kidney injury is a common and critical complication in patients with community-acquired pneumonia who are admitted to intensive care units, substantially increasing their risk of short-term mortality. To enhance early clinical decision-making, ...

Similarity as likelihood ratio: Coupling representations from machine learning (and other sources) with cognitive models.

Psychonomic bulletin & review
Similarity lies at the core of theories of memory and perception. To understand similarity relations among complex items like text and images, researchers often rely on machine learning to derive high-dimensional vector representations of those items...

Blastulation and ploidy prediction using morphology assessment in 33,999 day-3 embryos.

Scientific reports
Although contemporary practice in in vitro fertilization (IVF) favors embryo transfer at blastocyst stage, several centres worldwide employ cleavage-stage Day-3 embryo transfers. The advantage of cultures extended to Day-5 and beyond, is to ensure th...

Shared human-machine control of an intelligent bionic hand improves grasping and decreases cognitive burden for transradial amputees.

Nature communications
Bionic hands can replicate many movements of the human hand, but our ability to intuitively control these bionic hands is limited. Humans' manual dexterity is partly due to control loops driven by sensory feedback. Here, we describe the integration o...

Artificial intelligence-driven anthropometric assessment for young children: evaluating the accuracy and practicality of a digital image-based length and weight prediction tool.

BMJ health & care informatics
BACKGROUND: Monitoring early childhood growth is vital, as growth faltering could indicate nutritional or health issues requiring prompt intervention. Our study's aim was to assess the performance of a length-weight artificial intelligence (LWAI) too...

Digital Health Technologies: Learnings and Perspectives From a Patient Engagement Stakeholder Expectations Matrix Study.

Journal of medical Internet research
As digital health technologies become increasingly integrated into health care systems worldwide, there is growing recognition that their full potential can be realized only when development is rooted in patient engagement (PE). Despite its proven va...