Infectious Disease

BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature

The development of vision-language models (VLMs) is driven by large-scale and diverse multimodal datasets. However, progress toward generalist biomedical VLMs is limited by the lack of annotated, publicly accessible datasets across biology and medicine. Existing efforts are restricted to narrow domains, missing the full diversity of biomedical knowledge encoded in scientific literature. To addre...

Static Segmentation by Tracking: A Frustratingly Label-Efficient Approach to Fine-Grained Segmentation

We study image segmentation in the biological domain, particularly trait and part segmentation from specimen images (e.g., butterfly wing stripes or beetle body parts). This is a crucial, fine-grained task that aids in understanding the biology of organisms. The conventional approach involves hand-labeling masks, often for hundreds of images per species, and training a segmentation model to gene...

Using core genome and machine learning for serovar prediction in Salmonella enterica subspecies I strains.

This study presents a dual investigation of Salmonella enterica subspecies I, focusing on serovar prediction and core genome characteristics. We utili...

EquiBoost: An Equivariant Boosting Approach to Molecular Conformation Generation

Molecular conformation generation plays key roles in computational drug design. Recently developed deep learning methods, particularly diffusion mod...

Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection

This study presents a comparative analysis of methods for detecting COVID-19 infection in radiographic images. The images, sourced from publicly ava...

A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies or the opening or closing...

Enhanced Tuberculosis Bacilli Detection using Attention-Residual U-Net and Ensemble Classification

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a critical global health issue, necessitating timely diagnosis and treatment. Curre...

Efficient and Accurate Tuberculosis Diagnosis: Attention Residual U-Net and Vision Transformer Based Detection Framework

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, continues to be a major global health threat despite being preventabl...

Individualized multi-treatment response curves estimation using RBF-net with shared neurons.

Heterogeneous treatment effect estimation is an important problem in precision medicine. Specific interests lie in identifying the differential effect...

Human Gaze Boosts Object-Centered Representation Learning

Recent self-supervised learning (SSL) models trained on human-like egocentric visual inputs substantially underperform on image recognition tasks co...

Synthetic Fungi Datasets: A Time-Aligned Approach

Fungi undergo dynamic morphological transformations throughout their lifecycle, forming intricate networks as they transition from spores to mature ...

COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database

Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on...

From Images to Detection: Machine Learning for Blood Pattern Classification

Bloodstain Pattern Analysis (BPA) helps us understand how bloodstains form, with a focus on their size, shape, and distribution. This aids in crime ...

Accurate prediction of gene deletion phenotypes with Flux Cone Learning

Predicting the impact of gene deletions is crucial for biological discovery, biomedicine, and biotechnology. For example, identifying lethal deletions...

Nanopore- and AI-empowered microbial viability inference

The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from asse...

Large Language Model-assisted text mining reveals bacterial pathogen diversity

Compiling and characterising the diversity of bacterial pathogens of humans is a critical challenge to tackle infection risk, especially in the contex...

Exploring the genetic landscape of ciprofloxacin-induced DNA supercompaction in Escherichia coli

DNA-damaging antibiotics like ciprofloxacin induce extensive double-strand breaks in Escherichia coli, triggering the SOS response and leading to DNA ...

f-BGM enables fungi-specific genome mining in high accuracy and interpretability

Emerging artificial intelligence (AI)-based genome mining methods have revolutionized the paradigm of bacterial secondary metabolite (SM) discovery. F...

GLM-Prior: a nucleotide transformer model reveals prior knowledge as the driver of GRN inference performance

Gene regulatory network inference depends on high-quality prior-knowledge, yet curated priors are often incomplete or unavailable across species and c...

Signatures of soft selective sweeps predominate in the yellow fever mosquito Aedes aegypti

The Aedes aegypti mosquito is a vector for human arboviruses and zoonotic diseases, such as yellow fever, dengue, Zika, and chikungunya, and as such p...