AIMC Journal:
bioRxiv

Showing 211 to 220 of 4935 articles

Improving Data Quality, Model Transparency and Performance in Lung Histopathology with Explainable AI

bioRxiv Sep 21, 2026
Convolutional neural networks (CNNs) have shown strong capabilities for image analysis. However, deploying these models in medical settings is complicated by their limited transparency. Over recent years, many approaches have been developed to overco...
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Discriminating rare disease cases from their controls based on observed and excluded phenotypes

bioRxiv Sep 21, 2026
Rare diseases are individually uncommon but collectively prevalent. Their primary clinical challenge lies not in treatment but in diagnosis. In the early stages of clinical management, it is frequently unclear whether the observed phenotypes are asso...
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Reliability-guided meta-control in intuitive physics

bioRxiv Sep 21, 2026
Intuitive physical reasoning is an important part of daily life, but the computations underlying it remain debated. Some prominent accounts propose intuitive physics relies on mental simulation, with people evolving mental scenes forward through step...
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The activation function of CA3 pyramidal neurons is optimal for the stable recall of memory patterns

bioRxiv Sep 20, 2026
Hippocampal area CA3 is widely believed to serve a core memory function: retrieving distributed patterns of neural activity that were previously stored in the recurrent connections between neurons. However, it remains unknown how the physiological pr...
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Language-Model-Based Detection of Genetic Editing in Bacteria

bioRxiv Sep 20, 2026
Recent advances in genome editing allow easy genetic manipulation of bacteria, providing them with new traits, some of which could be hazardous, e.g. enhanced virulence or extended resistance to antibiotics. The ability to detect artificially modifie...
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Scaling Network Medicine with LLMs for Combinatorial Drug Repurposing in ER+ Breast Cancer

bioRxiv Sep 20, 2026
Drug repurposing can accelerate therapy discovery for ER+ breast cancer, but combination selection remains difficult. We developed an LLM-driven network medicine framework that extracts drug--target relationships from 595,122 PubMed abstracts, builds...
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StressNET: an adaptable deep-learning model for mechanical stress inference in tissues

bioRxiv Sep 20, 2026
Mechanical interactions between cells are fundamental to tissue morphogenesis during development and regeneration. Computational methods that infer intercellular stresses from microscopy images of cell shapes offer a non-invasive alternative to exper...
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Data-driven predictive design of engineered living hydrogels

bioRxiv Sep 18, 2026
Engineered living materials (ELMs) offer a promising route to biologically manufactured materials for healthcare, construction and manufacturing. However, their rational design is limited by the lack of quantitative relationships linking design param...
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Unraveling Environmental Drivers of Insect Pest Dynamics Across Multiple Landscapes

bioRxiv Sep 18, 2026
The persistence of pest populations during crop off-seasons is a major challenge for integrated pest management, yet the ecological processes underlying survival and re-infestation often remain unclear. We investigated the oriental fruit fly, Bactroc...
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Machine Learning for Toxicity Prediction in Low-Sample Molecular Classes

bioRxiv Sep 18, 2026
Deep learning models such as Chemprop have advanced quantitative molecular property prediction, but their reliance on large training sets limits use in data-scarce domains. We propose a framework that fine-tunes a general baseline model trained on pu...
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