Latest AI and machine learning research in transplantation for healthcare professionals.
Background The burden of new HIV infections and HIV-related deaths have declined dramatically in sub-Saharan Africa (SSA). However, current HIV surveillance systems are primarily donor-funded and rely on data from population-based surveys and routine health services. These need to evolve so that they can reliably monitor future HIV trajectory, in the context of declining burden of HIV and limited ...
Deciphering ultra-large-scale omics data with minimal resources while maintaining high computational efficiency is a longstanding challenge in biology. Here, we present Local Pooling (LP), a lightweight, ultrafast and general framework that leverage neighbor-indexing strategy and local pooling module to generate omics embedding and compatible with variety of downstream analyses. We developed its a...
Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual ce...
Pelvic diseases in women of reproductive age represent a major global health burden, with diagnosis frequently delayed due to high anatomical variabil...
A limitation of social contingency research with infants is that scientists can only instruct the caregivers to modulate their interactive behaviour w...
Digitizing large histopathology archives requires processing millions of scanned whole slide images that must be validated rapidly. Automated organ-of...
Background: Prognostic assessment in critically ill patients with cancer remains challenging, as conventional ICU severity scores often perform subopt...
Medical audio classification remains challenging due to low signal-to-noise ratios, subtle discriminative features, and substantial intra-class variab...
Accurate estimation of tacrolimus exposure, quantified by the area under the concentration-time curve (AUC), is essential for precision dosing after r...
Respiratory rate (RR) is a key vital sign for clinical assessment and mental well-being, yet it is rarely monitored in everyday life due to the lack o...
Multi-organ segmentation is a widely applied clinical routine and automated organ segmentation tools dramatically improve the pipeline of the radiolog...
Recently, data-centric AI methodology has been a dominant paradigm in single-cell transcriptomics analysis, which treats data representation rather th...
World models have demonstrated significant promise for data synthesis in autonomous driving. However, existing methods predominantly concentrate on si...
Precise localization with respect to a set of objects of interest enables mobile robots to perform various tasks. With the rise of edge devices capabl...
Longitudinal biomedical datasets, particularly high-resolution microbiome profiles, present unique and complex challenges arising from their extreme s...
Chemotherapy has been widely used in cancer treatment, but most of the chemotherapeutic drugs rely mainly on passive accumulation due to lack of targe...
Three-dimensional (3D) reconstruction of ships is an important part of maritime monitoring, allowing improved visualization, inspection, and decision-...
Speculative decoding (SD) has proven effective for accelerating LLM inference by quickly generating draft tokens and verifying them in parallel. Howev...
Automated patient positioning plays an important role in optimizing scanning procedure and improving patient throughput. Leveraging depth information ...
Cardiovascular diseases (CVD) are the leading cause of death worldwide, with coronary artery disease (CAD) comprising the largest subcategory of CVDs....