Bioterrorism

Predicting Drug Response with Multi-Task Gradient-Boosted Trees in Epilepsy

Despite the availability of numerous anti-seizure medications (ASMs), drug resistance remains a major issue for people with epilepsy. The probability of achieving seizure freedom diminishes with each unsuccessful drug trial, and the impact of genetic and clinical markers on ASM response remains unclear. To address this issue, we used state-of-the-art machine learning (ML) methods to predict the re...

DeepDiff-SHAP: Interpretable deep learning for subgroup-specific causal inference using conditional SHAP

Precision medicine aims to tailor healthcare strategies to individual differences in genetic, clinical, and environmental factors. However, identifying subgroup-specific causal relationships in complex biomedical data remains a major challenge, especially when standard causal inference methods average over population heterogeneity. We introduce DeepDiff-SHAP, a novel framework that combines regres...

Detection of multiple per- and polyfluoroalkyl substances (PFAS) using a biological brain-based gas sensor

Per- and polyfluoroalkyl substances (PFAS) are man-made compounds that bioaccumulate in environments. Current PFAS detection technologies encounter di...

Illuminating the Virosphere’s Dark Matter using Hierarchical Deep Learning

Systematic discovery of novel viruses is essential for pandemic preparedness, understanding tumor-associated viruses, developing viral delivery system...

Improved interpretability in LFADS models using a learned, context-dependent per-trial bias

The computation-through-dynamics perspective argues that biological neural circuits process information via the continuous evolution of their internal...

Integrated analysis implicates novel insights of NMB into lactate metabolism and immune response prediction in primary glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...

Functional organization and natural scene responses across mouse visual cortical areas revealed with encoding manifolds

A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challeng...

Finetuning Foundation Models for Temporal Clinical Transcriptomics Data

Timeseries clinical transcriptomic datasets offer the opportunity to gain insights into the dynamics of disease mechanisms/treatment responses. Howeve...

Machine Learning Ensemble Reveals Age-Specific Responses of Murine Mammary Tissue to Spaceflight With Relevance to Breast Cancer: An Observational Study

Spaceflight presents unique environmental stressors, such as microgravity and radiation, that significantly affect biological systems at the molecular...

mosna reveals different types of cellular interactions predictive of response to immunotherapies and survival in cancer

Spatially resolved omics enable the discovery of tissue organization of biological or clinical importance. Despite the existence of several methods, p...

A machine learning framework for supervised treatment response prediction from tumor transcriptomics: A large-scale pan-cancer study

Precision oncology aims to guide treatment decisions using biomarkers. While DNA-based panels are increasingly applied, RNA transcriptomics remain und...

SigSpace: an LLM-based agent for drug response signature interpretation

Agent systems powered by large language models (LLMs) are increasingly applied in computational biology to automate analysis, integrate data, and acce...

Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To...

A Context-Specific, Literature-Supported Framework for Validating Stress Response Models in Mammals

Computational models of stress responses can highlight candidate genes underlying physiological adaptation, but their utility depends on rigorous vali...

Stress Coping Style Alters Functional Brain Network Activity to Acute Stressor

Consistent individual differences in behavior (e.g., personality types, stress coping styles) are a common occurrence across animal taxa. One hypothes...

Personalized circulating tumor DNA dynamics predict survival and response to immune checkpoint blockade in recurrent/metastatic head and neck cancer

Recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) is an aggressive cancer with a median overall survival of only 12 months. Exist...

Collaborative intelligence in AI: Evaluating the performance of a council of AIs on the USMLE

The variability in responses generated by Large Language Models (LLMs) like OpenAI’s GPT-4 poses challenges in ensuring consistent accuracy on medical...

Strengths and Limitations of Using ChatGPT: A Preliminary Examination of Generative AI in Medical Education

Objective Structured Clinical Examinations (OSCEs) are critical tools in medical education, designed to evaluate clinical competence by engaging stude...

PREACT-digital: Study protocol for a longitudinal, observational multi-center study on wearable- and EMA- based predictors of non-response to CBT for internalizing disorders

Despite CBT’s status as a first-line treatment, a substantial proportion of patients does not experience sufficient symptom relief. Recent advances in...

Evaluating biomedical feature fusion on machine learning’s predictability and interpretability of COVID-19 severity types

Accurately differentiating severe from non-severe COVID-19 clinical types is critical for the healthcare system to optimize workflow. Current techniqu...