Community health workers (CHWs) in low-resource settings deliver variable-quality care. This study used OpenAI's o3 and Google's Gemini Flash 2.5 to evaluate whether large language models (LLMs) 'listening' to CHW-patient interactions could generate ... read more
Accurate monitoring of populations is essential for conservation management, including for vulnerable seabirds. Yet traditional ground-based surveys are logistically challenging and time-consuming, especially in remote environments such as the sub-An... read more
Predicting cellular responses to genetic and chemical perturbations remains a central challenge in single-cell biology and a key step toward building in silico virtual cells. The rapid growth of perturbation datasets and advances in deep-learning mod... read more
In this paper, we present a novel and efficient framework for cross-modality medical image synthesis, developed for BraSyn-Task 8. Our method combines the fast-sampling capabilities of the Fast-Denoising Diffusion Probabilistic Model (Fast-DDPM) with... read more
Accurate diagnosis of cardiac abnormalities from electrocardiogram signals remains a central challenge in automated cardiovascular assessment. This study investigates the efficiency of time-frequency representations and deep learning architectures in... read more
Compared to immortalized cell lines, patient-derived organoids and other ex vivo models have been shown to better recapitulate patient responses to therapy. High cost and technical complexity have prevented the creation of pan-cancer ex vivo datasets... read more
RNA interference (RNAi) is a crucial biological post-transcriptional gene silencing mechanism where small interfering RNA (siRNA) guides RNA-induced silencing complex (RISC) to bind with messenger RNA (mRNA) thereby silencing it and stopping protein ... read more
Microwell microfluidics has emerged as powerful platforms for high precision biological and chemical investigations, bridging microscale fluid handling with compartmentalized reaction environments. Achieving robust and reproducible performance in suc... read more
Spatial attention is often partitioned into endogenous, exogenous, and social forms, yet it remains unclear whether a single neural circuit can support all three and how their population codes are organized. Here we trained recurrent artificial neura... read more
We present p-Brain, an end-to-end neuroimaging analysis framework for reproducible, automated quantitative DCE-MRI analysis at scale. From standard acquisitions, p-Brain estimates baseline relaxation parameters, converts signal to gadolinium concentr... read more
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