Latest AI and machine learning research in tuberculosis for healthcare professionals.
Tuberculosis (TB) is a major global health challenge, with many cases remaining undiagnosed due to limited access to screening and diagnostic services. Artificial intelligence (AI) systems based on cough sound analysis offer a scalable and accessible approach to TB screening, but most previous studies have analysed isolated cough events, despite the possibility that diagnostically useful informati...
Blood-based biomarkers discovered by machine learning often lack disease specificity and cross-population robustness for clinical applications. We describe a biomarker discovery strategy that exploits monocytes as circulating sentinels to amplify disease-perturbed signals in blood. This strategy leverages monocyteMINER, a mechanistic transcriptional regulatory network inferred from monocyte transc...
Abstract Climate change is altering environmental conditions that influence foodborne disease transmission, yet traditional systematic reviews cannot ...
Machine learning (ML) has accelerated molecular discovery, yet training models to generalize to out-of-distribution (OOD) chemical spaces remains fund...
Background: Tuberculosis, especially drug-resistant tuberculosis (DR-TB) including multidrug-resistant (MDR) and extensively drug-resistant (XDR) stra...
Empathy enables individuals to attune to others' experiences through shared affective, sensorimotor, and neural representations, but its influence on ...
Accurate computational reconstruction of bacterial transcriptional regulatory network (TRN) from sequence information alone remains a fundamental chal...
High-resolution Diffusion Transformer (DiT) inference contains substantial spatial redundancy, but many spatially adaptive implementations encode regi...
Humans handle numbers nimbly, suggesting a richer neural manifold structure than the prevalent mental number line model. In populations of medial temp...
While WGS-based AMR prediction has reached high accuracy, existing models lack a mechanism to ground neural attributions in established biological pat...
Light microscopy of tissue sections stained with hematoxylin and eosin (H&E) has been the foundation of histopathology for over 150 years and remains ...
Small aerial robots are particularly well-suited for search and rescue in confined and hazardous environments due to their agility, low cost, and abil...
Tuberculosis remains a leading cause of infectious disease mortality, and the continued emergence of drug-resistant Mycobacterium tuberculosis strains...
Background Community-wide active case-finding (ACF) is being increasingly implemented as a tuberculosis (TB) elimination intervention. However, conven...
Ab initio prediction of side effect frequencies is important for assessing the risk-benefit profile of drugs and for identifying potential adverse eff...
Tuberculosis (TB) continues to pose a significant global public health challenge with substantial morbidity and mortality. Current TB biomarkers lack ...
We augment the Slotine--Li adaptive controller for Euler--Lagrange systems with three learned components: a structured-quadratic Lyapunov function \(V...
Real-world image degradation is often unknown, spatially non-uniform, and compositional, requiring all-in-one restoration models to adapt a single set...
Purpose: Assessing visual function in patients with ultra-low vision (ULV), particularly those with retinitis pigmentosa (RP), remains a significant c...
Simulating optical tactile sensors presents significant challenges due to their high deformability and intricate optical properties. To address these ...