Annual review of analytical chemistry (Palo Alto, Calif.)
Feb 27, 2025
Tandem mass spectrometry (MS/MS) is crucial for small-molecule analysis; however, traditional computational methods are limited by incomplete reference libraries and complex data processing. Machine learning (ML) is transforming small-molecule mass s...
ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (Copilot, GPT-3.5, and GPT-4) on antimalarial use in systemic lupus erythematosus (SLE).Materials and MethodsWe utilized 13 questions derived from pati...
The combination of Ca overload and reactive oxygen species (ROS) production for cancer therapy offers a superior solution to the lack of specificity in traditional antitumor strategies. However, current therapeutic platforms for this strategy are pri...
The integration of artificial intelligence (AI) into rheumatology has revolutionized research and clinical practice, offering transformative advancements in diagnostics, biomarker discovery, genomics, digital health technologies, and personalized med...
BACKGROUND AND AIMS: The digitalization of gambling provides unprecedented opportunities for early identification of problem gambling, a well-recognized public health issue. This study aimed to advance current practices by employing advanced machine ...
Associative learning tests are cognitive assessments that evaluate the ability of individuals to learn and remember relationships between pairs of stimuli. The Rutgers Acquired Equivalence Test (RAET) is an associative learning test that utilizes ima...
The increase in antimicrobial resistance presents a major challenge in treating bacterial infections, underscoring the need for innovative drug discovery approaches and novel inhibitors. Bacterial RNA polymerase (RNAP) has emerged as a crucial target...
Deep learning models have advanced our ability to predict cell-type-specific chromatin patterns from transcription factor (TF) binding motifs, but their application to perturbed contexts remains limited. We applied transfer learning to predict how co...
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