Results 31 to 40 of about 10,079,567 (236)
Cross-Attention Mechanism for Medical Visual Question Answering
Visual Question Answering (VQA) is a machine learning task that aims to create systems capable of answering natural language questions based on given images.
Nada Fadhil Mohammed, Israa H. Ali
doaj +1 more source
An Open-Domain Question Answering System Using Annotated Web Feeds. [PDF]
Open Domain Question Answering Systems (ODQA) aim to answer all possible questions, regardless of topic and time. For this to be possible, most current ODQA systems depend on the World Wide Web through search engines, e.g.
Cheah, Yu-N +3 more
core +1 more source
ICT-DCU question answering task at NTCIR-6 [PDF]
This paper describes details of our participation in the NTCIR-6 Chinese-to-Chinese Question Answering task. We use the “retrieval plus extraction approach” to get answers for questions.
Bin Wang +5 more
core +2 more sources
Evaluation a of a layered approach to question answering over linked data [PDF]
Walter S, Unger C, Cimiano P, Bär D. Evaluation a of a layered approach to question answering over linked data. Presented at the The 11th International Semantic Web Conference (ISWC 2012), Boston, USA.We present a question answering system architecture ...
Christina Unger +10 more
core +1 more source
Automatic Chart Understanding: A Review
Automated chart analysis has vast potential to improve the accessibility of charts for a wider audience, e.g., people with visual impairments or other disabilities, by generating captions for chart images that can quickly convey the information being ...
Ali Mazraeh Farahani +4 more
doaj +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Generative Models in Medical Visual Question Answering: A Survey
Medical Visual Question Answering (MedVQA) is a crucial intersection of artificial intelligence and healthcare. It enables systems to interpret medical images—such as X-rays, MRIs, and pathology slides—and respond to clinical queries.
Wenjie Dong +5 more
doaj +1 more source
Spatial biology in cancer epigenetics
Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
wiley +1 more source
The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley +1 more source
Glioblastoma cells express calcitonin receptor variants (CT receptor isoforms) that may help them survive stress. Using qPCR, transcript‐specific long‐read nanopore sequencing, immunofluorescence co‐localisation and comparative sequence analysis, this study identifies a novel alternatively spliced CALCR transcript that encodes the CTb receptor isoform ...
Pragya Gupta +7 more
wiley +1 more source

