Latest AI and machine learning research in infectious disease for healthcare professionals.
Irregular multivariate time series with missing values present significant challenges for predictive modeling in domains such as healthcare. While deep learning approaches often focus on temporal interpolation or complex architectures to handle irregularities, we propose a simpler yet effective alternative: extracting time-agnostic summary statistics to eliminate the temporal axis. Our method comp...
Bacterial proteins are specialized with extensive functional diversity for survival in diverse and stressful environments. A significant portion of these proteins remains functionally uncharacterized, limiting our understanding of bacterial survival mechanisms. Hence, we developed Deep Expression STructure (DeepEST), a multimodal deep learning framework designed to accurately predict protein funct...
Mobile genetic elements and genomic islands (GIs) frequently encode antibiotic resistance and host-adaptation cargo, yet routine genome comparison pip...
Banana and plantain (Musa spp.) production in Sub-Saharan Africa is severely constrained by multiple diseases, with Banana bunchy top virus (BBTV) rep...
Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical bottlenecks: the near-quadratic cost of pairwise ...
Assessing the human infection potential of emerging coronaviruses remains a critical challenge for global health preparedness. In this study, we devel...
Here, we introduce Detectrons, modular biosensors that couples programmable toehold switches with retron-mediated reverse transcription to transduce R...
Eukaryotic cells are spatially organized into functionally-distinct compartments. This three-dimensional(3D) organization generates intracellular hete...
Safe and interpretable sequential decision-making is critical in healthcare, yet reinforcement learning (RL) policies for sepsis treatment optimizatio...
Recent advances in diffusion models have enabled powerful image editing capabilities guided by natural language prompts, unlocking new creative possib...
Recent advances in machine learning (ML)-based protein design methods have enabled the rapid in silico generation of large libraries of miniprotein bi...
Bedaquiline resistance is emerging globally and threatens the effectiveness of the novel short all-oral regimens for rifampicin-resistant tuberculosis...
Accurately characterising mosquito infection dynamics is essential for effective dengue prevention and control, yet these dynamics are rarely observab...
Data-independent acquisition (DIA) proteomics enables reproducible, large-scale protein identification and quantification but remains challenging to a...
Machine learning (ML) approaches applied to Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) spectra have s...
In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy. A...
Wastewater-based epidemiology provides a low-cost, scalable view of community infection dynamics, but converting these signals into actionable epidemi...
Bacterial infections are a major cause of morbidity and mortality among children under five in low- and middle-income countries (LMICs). Children in L...
Antimicrobial resistance (AMR) is a growing global health crisis, responsible for an estimated 1.27 million deaths in 2019 alone. traditional approach...
Background: Liver cancer primarily develops in patients with chronic liver disease (CLD), yet most cases are diagnosed at an advanced stage with poor ...