Clinicians usually combine information from multiple sources to achieve the
most accurate diagnosis, and this has sparked increasing interest in leveraging
multimodal deep learning for diagnosis. However, in real clinical scenarios,
due to differen... read more
Text-to-video retrieval requires precise alignment between language and
temporally rich video signals. Existing methods predominantly exploit visual
cues and often overlook complementary audio semantics or adopt coarse fusion
strategies, leading to... read more
Aneurysmal subarachnoid hemorrhage (SAH) is a life-threatening neurological
emergency with mortality rates exceeding 30%. Transfer learning from related
hematoma types represents a potentially valuable but underexplored approach.
Although Unet arch... read more
Electronic health records (EHRs) contain rich unstructured clinical notes
that could enhance predictive modeling, yet extracting meaningful features from
these notes remains challenging. Current approaches range from labor-intensive
manual clinicia... read more
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant field in the domain of affective computing where EEG signals are the cause of reliable and objective applications. Despite these advancements, signific... read more
Raman spectroscopy is an enticing tool for the rapid identification of pathogenic bacteria and has the potential to meet the demand for early diagnosis and timely treatment of patients. However, it remains a challenge to devise a reliable Raman detec... read more
Accurate prediction of protein-ligand interactions is essential for
computer-aided drug discovery. However, existing methods often fail to capture
solvent-dependent conformational changes and lack the ability to jointly learn
multiple related tasks... read more
Vision Transformers (ViTs) have revolutionized computer vision tasks with
their exceptional performance. However, the introduction of privacy regulations
such as GDPR and CCPA has brought new challenges to them. These laws grant
users the right to ... read more
The rapid evolution of deepfake generation techniques demands robust and
accurate face forgery detection algorithms. While determining whether an image
has been manipulated remains essential, the ability to precisely localize
forgery artifacts has ... read more
A growing body of literature supports the association between ambient particulate pollution and the risk of type 2 diabetes (T2DM). Both issues are particularly relevant in Italy. This study investigates the relationship between T2DM and exposure to ... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.