Latest AI and machine learning research in hiv/aids for healthcare professionals.
Antiphospholipid syndrome (APS) and systemic sclerosis (SSc) are immune-mediated multisystem autoimmune diseases with distinct clinical phenotypes but overlapping pathogenic themes, including immune dysregulation, chronic inflammation, and endothelial injury. Using peripheral blood transcriptome datasets from the Gene Expression Omnibus (GSE102215: 9 APS/9 controls; GSE231691: 49 SSc/18 controls),...
Food wastage is one of the critical challenges in the agricultural supply chain, and accurate and effective spoilage detection can help to reduce it. Further, it is highly important to forecast the spoilage information. This aids the longevity of the supply chain management in the agriculture field. This motivated us to propose fusion based architectures by combining CNN with LSTM and DeiT transfo...
Lumpy Skin Disease (LSD) and Foot-and-Mouth Disease (FMD) are highly contagious viral diseases affecting cattle, causing significant economic losses a...
Large language models (LLMs) have shown remarkable success in natural language processing, prompting interest in their application to genomic sequence...
The accurate identification of antiviral peptides (AVPs) is crucial for novel drug development. However, existing methods still have limitations in ca...
Images captured in hazy and smoky environments suffer from reduced visibility, posing a challenge when monitoring infrastructures and hindering emerge...
Accurately predicting how amino acid substitutions alter protein function is a central challenge in biology, with applications from interpreting disea...
Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs)...
Large language models (LLMs) have taken the natural language processing (NLP) domain by storm, and their transformative momentum has surged into the d...
The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting cruci...
Image sensors are integral to a wide range of safety- and security-critical systems, including surveillance infrastructure, autonomous vehicles, and...
Medical Hyperspectral Imaging (MHSI) has emerged as a promising tool for enhanced disease diagnosis, particularly in computational pathology, offeri...
Increasingly massive volumes of multi-modal data are being accumulated in many {real world} settings, including in health care and e-commerce. This ...
Inconsistencies between clinical and omics data may arise within medical cohorts. The identification, annotation and explanation of anomalous omics-...
Neural Radiance Fields (NeRF) have recently emerged as a paradigm for 3D reconstruction from multiview satellite imagery. However, state-of-the-art ...
Image logs are crucial in capturing high-quality geological information about subsurface formations. Among the various geological features that can ...
HIV epidemiological data is increasingly complex, requiring advanced computation for accurate cluster detection and forecasting. We employed quantum...
Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and i...
In recent years, cytopathology practices increasingly are considering the adoption of digital modalities to support remote rapid on-site evaluation (R...
Recently, large pre-trained models (LPM) have achieved great success, which provides rich feature representation for downstream tasks. Pre-training an...