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In critical decision support systems based on medical imaging, the reliability of AI-assisted decision-making is as relevant as predictive accuracy. Although deep learning models have demonstrated significant accuracy, they frequently…
Advance designs of random lasers towards development of miniature laser systems are in demand. We demonstrated random lasing from Rhodamine-B dye attached to polystyrene micro-spheres. Bare polystyrene spheres were used as scatterers and…
Plasmonic metamaterials can be used to enhance mid-infrared sensors and detectors for immunosensing applications. The major challenge is to integrate these technologies in low-cost, compact, and promising platforms. In this study, as an…
With the increasing demand for personalized health monitoring, wearable sensors have gained attention in medical diagnostics and physiological tracking. Hydrogels, known for their mechanical properties and similarity to biological tissues,…
The integrity of the reconstructed human epidermis generated in vitro could be assessed using histological analyses combined with immunohistochemical staining of keratinocyte differentiation markers. Computer-based analysis of scanned…
Achieving efficient, high-fidelity, high-resolution garment simulation is challenging due to its computational demands. Conversely, low-resolution garment simulation is more accessible and ideal for low-budget devices like smartphones. In…
Tight-binding (TB) molecular dynamics (MD) has emerged as a powerful method for investigating the atomic-scale structure of materials --- in particular the interplay between structural and electronic properties --- bridging the gap between…
Recently, bacterial nanocellulose (BNC), a biological material produced by non-pathogenic bacteria that possesses excellent material properties for various medical applications, has received increased interest as a carrier system for drug…
Automated segmentation of tuberculosis (TB)-consistent lesions in chest X-rays (CXRs) using deep learning (DL) methods can help reduce radiologist effort, supplement clinical decision-making, and potentially result in improved patient…
Accurate identification of drug-target interactions (DTI) remains a central challenge in computational pharmacology, where sequence-based methods offer scalability. This work introduces a sequence-based drug-target interaction framework…
Learning fine-grained embeddings from coarse labels is a challenging task due to limited label granularity supervision, i.e., lacking the detailed distinctions required for fine-grained tasks. The task becomes even more demanding when…
In this work, a new method for automatically extending Bounding Box (BB) and mask labels across different channels on multilens cameras is presented. For that purpose, the proposed method combines the well known phase correlation method…
Infrared and visible image fusion has been developed from vision perception oriented fusion methods to strategies which both consider the vision perception and high-level vision task. However, the existing task-driven methods fail to…
Current neural networks for predictions of molecular properties use quantum chemistry only as a source of training data. This paper explores models that use quantum chemistry as an integral part of the prediction process. This is done by…
Multimodal deep learning has been used to predict clinical endpoints and diagnoses from clinical routine data. However, these models suffer from scaling issues: they have to learn pairwise interactions between each piece of information in…
The emergence of virtual staining technology provides a rapid and efficient alternative for researchers in tissue pathology. It enables the utilization of unlabeled microscopic samples to generate virtual replicas of chemically stained…
Comparative molecular dynamics simulations of a hexamer cluster of the protic ionic liquid ethylammonium nitrate are performed using density functional theory (DFT) and density functional-based tight binding (DFTB) methods. The focus is on…
Our growing ability to tailor healthcare to the needs of individuals has the potential to transform clinical treatment. However, the measurement of multiple biomarkers to inform clinical decisions requires rapid, effective, and affordable…
Bacterial biofilms underlie many persistent infections, posing major hurdles in antibiotic treatment. Here, we design and demonstrate tug-of-war optical tweezers that can facilitate assessment of cell-cell adhesion - a key contributing…
Skin lesion identification is a key step toward dermatological diagnosis. When describing a skin lesion, it is very important to note its body site distribution as many skin diseases commonly affect particular parts of the body. To exploit…