AIMC Topic: Machine Learning

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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...

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...

Discrimination of Citri reticulatae pericarpium (CP) and Citrus reticulata 'chachi' (GCP): Focus on HPTLC, UHPLC techniques combined with machine learning and content differences of three specific flavonoids.

Journal of chromatography. A
The global consumption of Citri reticulatae pericarpium (Chenpi, CP) and Citrus reticulata 'chachi' (Guangchenpi, GCP) has been experiencing a steady increase, driven by its extensive applications in healthcare, flavoring, and therapeutic fields. Whi...

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...

Machine Learning-Assisted False Positive Detection in Metabolite Identification Workflows.

Analytical chemistry
Metabolite identification is a pivotal step in drug discovery and development, enabling the comprehensive analysis of drug-derived compounds within biological systems. However, the complexity of liquid chromatography-mass spectrometry data often resu...

Prompt-CBP: A Novel Prompt Learning-Based Model for Predicting Cross-Species Promoters.

Journal of chemical information and modeling
Promoter sequences across species exhibit both specificity and conservation. The specificity of promoter sequences typically leads to lower cross-species prediction performance compared to within-species prediction. However, conserved promoter motifs...

Can AI-Predicted Complexes Teach Machine Learning to Compute Drug Binding Affinity?

Journal of chemical information and modeling
We evaluate the feasibility of using co-folding models for synthetic data augmentation in training machine learning-based scoring functions (MLSFs) for binding affinity prediction. Our results show that performance gains depend critically on the stru...

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...