AIMC Topic: Humans

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A Transformer-Based Deep Learning Approach to Predicting Air Organic Pollutant-Human Protein Interactions.

Environmental science & technology
Air pollution poses a critical global public health challenge. Molecular-level initiating events, such as pollutant-protein interactions, can trigger cascades of biological responses that may contribute to adverse health effects. However, current met...

Evaluating large language models in biomedical data science challenges through a classroom experiment.

Proceedings of the National Academy of Sciences of the United States of America
Large language models (LLMs) have shown remarkable capabilities in algorithm design, but their effectiveness in solving data science challenges in real-world settings remains poorly understood. We conducted a classroom experiment in which graduate st...

When does machine learning outperform clinicians? A comparison of prediction accuracy for PTSD treatment outcomes.

Psychological medicine
BACKGROUND: Machine learning (ML) models show promise in predicting post-traumatic stress disorder (PTSD) treatment outcomes, but it is unknown how their predictions compare to those of clinicians. This study directly compared the accuracy of clinici...

Investigation of data-driven stopping power calibration of treatment planning x-ray CT from simulated sparse-view proton radiographies.

Physics in medicine and biology
Proton therapy treatment planning currently needs to account for relatively large range uncertainty margins primarily due to the semi-empirical calibration of the treatment planning x-ray computed tomography (CT) to proton stopping power relative to ...

The best from both disciplines: integrating human and microbial signatures from whole genome sequencing to advance cancer diagnostics.

mSystems
Liquid biopsies are transforming oncology, enabling earlier diagnosis, dynamic treatment guidance, and personalized precision medicine, yet current approaches focusing mainly on circulating host cell-free DNA (cfDNA) neglect crucial information withi...

Decoding strategies for enhancing immunotherapy in head and neck squamous cell carcinoma.

International immunopharmacology
Immune checkpoint inhibitors have partially improved treatment outcomes for patients with head and neck squamous cell carcinoma (HNSCC), but the response rate remains low, with only a few patients benefiting. Mechanistically, HNSCC tumor cells often ...

Machine Learning for Neurotransmitter Monitoring by Fast Voltammetry: Current and Future Prospects.

ACS chemical neuroscience
Chemical neuroscience wields tools to uncover the molecular mysteries of the brain. Sensors can be fabricated with properties tailored to the scales needed to decode neurochemical information. Current instrumentation is capable of measurement rates t...

Predicting prolonged dalbavancin exposure using machine learning: a validated strategy for individualized redosing.

Antimicrobial agents and chemotherapy
Dalbavancin is a long-acting lipoglycopeptide increasingly used off-label for complex Gram-positive infections requiring prolonged therapy. Its extended half-life enables simplified regimens, but interindividual pharmacokinetic variability and pathog...

Breakthroughs of ultrasound-targeted microbubble destruction in treating myocardial ischemia-reperfusion injury: from angiogenesis regulation to precise inflammation suppression.

Drug delivery
Myocardial ischemia-reperfusion injury (MIRI), a frequent complication in acute myocardial infarction (AMI) treatment, arises from complex mechanisms including oxidative stress, inflammation, and mitochondrial dysfunction, which impair myocardial rep...

Fingerprint-Based Machine Learning for SARS-CoV-2 and MERS-CoV Inhibition: Highlighting the Potential of Bayesian Neural Networks.

Journal of chemical information and modeling
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) are two important targets in current drug discovery, mainly due to the COVID-19 pandemic and the MERS-CoV outbreaks in recent yea...