AIMC Topic: Humans

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Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.

Critical care explorations
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not t...

Bridging the human-AI knowledge gap through concept discovery and transfer in AlphaZero.

Proceedings of the National Academy of Sciences of the United States of America
AI systems have attained superhuman performance across various domains. If the hidden knowledge encoded in these highly capable systems can be leveraged, human knowledge and performance can be advanced. Yet, this internal knowledge is difficult to ex...

Neural Network With Attention Mechanism for Abnormality Detection and Localization in Diffusive Molecular Communication.

IEEE transactions on nanobioscience
Diffusive molecular communication (DMC) is an emerging paradigm in nanotechnology, which provides biocompatibility and nanoscale communication for many promising applications, such as targeted drug delivery, environmental monitoring, etc. However, de...

Demographic bias of expert-level vision-language foundation models in medical imaging.

Science advances
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can detect a broad spectrum of pathologies without relying on explicit trainin...

Learning the rules of peptide self-assembly through data mining with large language models.

Science advances
Peptides are ubiquitous and important biomolecules that self-assemble into diverse structures. Although extensive research has explored the effects of chemical composition and exterior conditions on self-assembly, a systematic study consolidating the...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

Medicina (Kaunas, Lithuania)
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...

Machine Learning-Guided Screening and Molecular Docking for Proposing Naturally Derived Drug Candidates Against MERS-CoV 3CL Protease.

International journal of molecular sciences
In this study, we utilized machine learning techniques to identify potential inhibitors of the MERS-CoV 3CL protease. Among the models evaluated, the Random Forest (RF) algorithm exhibited the highest predictive performance, achieving an accuracy of ...

Physiological Sensor Modality Sensitivity Test for Pain Intensity Classification in Quantitative Sensory Testing.

Sensors (Basel, Switzerland)
Chronic pain is prevalent and disproportionately impacts adults with a lower quality of life. Although subjective self-reporting is the "gold standard" for pain assessment, tools are needed to objectively monitor and account for inter-individual diff...

[Artificial intelligence in Public Health: opportunities, ethical challenges and future perspectives].

Revista espanola de salud publica
Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze large volumes of data in real time enhances epidemiological surveillance, optimizes healthcare resou...

Integrating Deep Learning Models with Genome-Wide Association Study-Based Identification Enhanced Phenotype Predictions in Group A .

Journal of microbiology and biotechnology
Group A (GAS) is a major pathogen with diverse clinical outcomes linked to its genetic variability, making accurate phenotype prediction essential. While previous studies have identified many GAS-associated genetic factors, translating these finding...