For clinical treatment, the accurate segmentation of lesions from dermoscopic images is extremely valuable. Convolutional neural networks (such as U-Net and its numerous variants) have become the main methods for skin lesion segmentation in recent ye...
Deep learning (DL) models find increasing application in mental state decoding, where researchers seek to understand the mapping between mental states (e.g., experiencing anger or joy) and brain activity by identifying those spatial and temporal feat...
OBJECTIVE: Quantitative measurements of trigonocephaly can be used to characterize and track this phenotype, which is associated with metopic craniosynostosis. Traditionally, trigonocephaly metrics were extracted from CT scans; however, this method e...
IEEE journal of biomedical and health informatics
Apr 4, 2023
The lack of a gold standard synergy quantification method for chemotherapeutic drug combinations warrants the consideration of different synergy metrics to develop efficient predictive models. Furthermore, neglecting combination sensitivity may lead ...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 3, 2023
Many high-performance DTA deep learning models have been proposed, but they are mostly black-box and thus lack human interpretability. Explainable AI (XAI) can make DTA models more trustworthy, and allows to distill biological knowledge from the mode...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 3, 2023
Automated recognition of Human Phenotype Ontology (HPO) terms from clinical texts is of significant interest to the field of clinical data mining. In this study, we develop a combined deep learning method named PhenoBERT for this purpose. PhenoBERT u...
The analysis of 3D microscopic cell culture images plays a vital role in the development of new therapeutics. While 3D cell cultures offer a greater similarity to the human organism than adherent cell cultures, they introduce new challenges for autom...
Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lungs has been investigated in various studies using artificial intelligence-based (AI) methods. However, an extensive analysis of state-of-the-art Convol...
The risks of post trauma complications are regulated by the injury, comorbidities, and the clinical trajectories, yet prediction models are often limited to single time-point data. We hypothesize that deep learning prediction models can be used for r...
In recent years, considerable work has been conducted on the development of synthetic medical images, but there are no satisfactory methods for evaluating their medical suitability. Existing methods mainly evaluate the quality of noise in the images,...
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