STDs

A collaborative submission model for building high-quality data resources at scale through partnership

Community data resources that aggregate datasets across studies are critical infrastructure for modern biomedical research, enabling large-scale analysis and the development of Artificial Intelligence (AI) models. However, building these resources involves a fundamental tension: the desire for a large corpus is often at odds with the need for richness and quality in both data and metadata. We deta...

Symb-xMIL: Symbolic Explanations for Multiple Instance Learning in Digital Pathology

Explanations of multiple instance learning (MIL) models are widely used for validation and discovery in digital histopathology. Existing methods primarily rely on heatmaps that highlight influential regions but do not explain how evidence from different tissue regions is combined to produce a prediction. This limits interpretability, especially when decisions depend on interactions between tissue ...

Genomic Diagnostics for Drug-Resistant Mycobacterium tuberculosis: Computational Prediction of Antimicrobial Resistance

Tuberculosis remains a leading cause of infectious disease mortality, and the continued emergence of drug-resistant Mycobacterium tuberculosis strains...

Spatio-temporal machine learning for multi-horizon prediction of bluetongue outbreaks

Reliable early warning of infectious disease outbreaks remains a major challenge for surveillance systems, particularly for vector-borne pathogens who...

A Bioprinted Head and Neck Cancer Organoid-Based Platform for Evaluating Multimodal Therapies

Treatment of advanced head and neck squamous cell carcinoma (HNSCC) often involves radiotherapy combined with chemotherapy, targeted therapy, or immun...

Histopathology-inferred spatial transcriptomics characterizes the tumor microenvironment in 1,500 head and neck tumors and predicts clinical outcomes

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy associated with poor prognosis despite recent therapeutic advances. We hypothes...

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone

Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language mod...

Deep Learning-Based Structure Modeling of the Treponema pallidum Proteome: Insights into Pathogenesis and Syphilis Vaccine Development

Treponema pallidum ssp. pallidum, the causative agent of syphilis, has a small proteome and encompasses numerous strains. Knowledge gaps remain in und...

Lost in State Space: Probing Frozen Mamba Representations

Mamba's recurrent state h_t is, by construction, a compressed summary of every token seen so far. This raises a tempting hypothesis: if we extract tok...

Deep-testing: the case of dependence detection

Deep learning methods have proved highly effective for classification and image recognition problems. In this paper, we ask whether this success can b...

Integrating Metabolic Networks into Hybrid Bioprocess Models

The optimization and control of bioprocesses require robust in silico models that can accurately capture the complex and dynamic behavior of living ce...

AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer

Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is curren...

PerturbationDrive: A Framework for Perturbation-Based Testing of ADAS

Advanced driver assistance systems (ADAS) often rely on deep neural networks to interpret driving images and support vehicle control. Although reliabl...

Predicting 5-Year Breast Cancer Risk from Longitudinal Digital Breast Tomosynthesis: A Single-center Retrospective Study

Background: Imaging-based breast cancer risk prediction models primarily use full-field digital mammography (FFDM). As digital breast tomosynthesis (D...

Machine Learning Enabled Smartphone CRISPR-Cas12a Lateral Flow Platform for Sensitive Detection of Circulating HPV DNA

Persistent infection with high-risk human papillomavirus (HPV) is the primary cause of cervical cancer and other HPV-related malignancies. Effective s...

Fair Lung Disease Diagnosis from Chest CT via Gender-Adversarial Attention Multiple Instance Learning

We present a fairness-aware framework for multi-class lung disease diagnosis from chest CT volumes, developed for the Fair Disease Diagnosis Challenge...

Beyond Attention Heatmaps: How to Get Better Explanations for Multiple Instance Learning Models in Histopathology

Multiple instance learning (MIL) has enabled substantial progress in computational histopathology, where a large amount of patches from gigapixel whol...

SYNAPSE: Framework for Neuron Analysis and Perturbation in Sequence Encoding

In recent years, Artificial Intelligence has become a powerful partner for complex tasks such as data analysis, prediction, and problem-solving, yet i...

Evaluating the AI Potential as a Safety Net for Diagnosis: A Novel Benchmark of Large Language Models in Correcting Diagnostic Errors

Background: Diagnostic errors are a leading cause of preventable patient harm, often occurring during early clinical encounters where diagnostic uncer...

Benchmarking Large Language Models for Intensive Care Unit Clinical Decision Support: A Dual Safety Evaluation of 26 Models on Consumer Hardware

Background: Large Language Models (LLMs) show promise for clinical decision support in Intensive Care Units (ICU), but their safety and reliability re...