Latest AI and machine learning research in prescriptions for healthcare professionals.
Interpreting the effects of variants within the human genome and proteome is essential for analysing disease risk, predicting medication response, and developing personalised health interventions. Due to the intrinsic similarities between the structure of natural languages and genetic sequences, natural language processing techniques have demonstrated great applicability in computational variant...
The Segment Anything Model (SAM) has revolutionized open-set interactive image segmentation, inspiring numerous adapters for the medical domain. However, SAM primarily relies on sparse prompts such as point or bounding box, which may be suboptimal for fine-grained instance segmentation, particularly in endoscopic imagery, where precise localization is critical and existing prompts struggle to ca...
With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these techn...
Protein-protein interaction (PPI) prediction is an instrumental means in elucidating the mechanisms underlying cellular operations, holding signific...
Current deep learning (DL)-based palmprint verification models rely on centralized training with large datasets, which raises significant privacy co...
Journaling plays a crucial role in managing chronic conditions by allowing patients to document symptoms and medication intake, providing essential ...
We present TopoMortar, a brick wall dataset that is the first dataset specifically designed to evaluate topology-focused image segmentation methods,...
Predicting clinical outcomes from preclinical data is essential for identifying safe and effective drug combinations. Current models rely on structu...
Objective: we propose a procedure for calibrating 4 parameters governing the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model der...
Biomedical visual question answering (VQA) has been widely studied and has demonstrated significant application value and potential in fields such a...
Drug combinations are required to treat advanced cancers and other complex diseases. Compared with monotherapy, combination treatments can enhance eff...
As part of the drug repurposing process, it is imperative to predict the interactions between drugs and target proteins in an accurate and efficient m...
Predicting long non-coding RNA (lncRNA)-protein interactions is essential for understanding biological processes and discovering new therapeutic targe...
Non-coding RNAs (ncRNAs) play crucial roles in drug resistance and sensitivity, making them important biomarkers and therapeutic targets. However, pre...
Cancer is a major public health problem while liver cancer is the main cause of global cancer-related deaths. The previous study demonstrates that the...
Understanding consumer choice is fundamental to marketing and management research, as firms increasingly seek to personalize offerings and optimize ...
Integrating LLM models into educational practice fosters personalized learning by accommodating the diverse behavioral patterns of different learner...
Hypertensive retinopathy (HR) is a severe eye disease that may cause permanent vision loss if not diagnosed early. Traditional diagnostic methods ar...
The rapid development of artificial intelligence (AI) has significantly transformed human-computer interactions, making it essential to establish ro...
Speech-comprehension difficulties are common among older people. Standard speech tests do not fully capture such difficulties because the tests poor...