Latest AI and machine learning research in prescriptions for healthcare professionals.
Recently, research into chatbots (also known as conversational agents, AI agents, voice assistants), which are computer applications using artificial intelligence to mimic human-like conversation, has grown sharply. Despite this growth, sociology lags other disciplines (including computer science, medicine, psychology, and communication) in publishing about chatbots. We suggest sociology can adv...
Knowledge of protein-ligand binding sites (LBSs) is crucial for advancing our understanding of biology and developing practical applications in fields such as medicine or biotechnology. PrankWeb is a web server that allows users to predict LBSs from a given three-dimensional structure. It provides access to P2Rank, a state-of-the-art machine learning tool for binding site prediction. Here, we pres...
Medication recommendation is a crucial task in healthcare, especially for patients with complex medical conditions. However, existing methods often ...
Advanced Encryption Standard (AES) is a widely adopted cryptographic algorithm, yet its practical implementations remain susceptible to side-channel...
The execution of effective and imperceptible personality assessments is receiving increasing attention in psychology and human-computer interaction ...
Most GCN-based methods model interacting individuals as independent graphs, neglecting their inherent inter-dependencies. Although recent approaches...
In this paper, we address the following question: How do generic foundation models (e.g., CLIP, BLIP, LLaVa, DINO) compare against a domain-specific...
The data appetite for Vision-Language Models (VLMs) has continuously scaled up from the early millions to billions today, which faces an untenable t...
Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an...
This work presents a comprehensive theory of consciousness grounded in mathematical formalism and supported by clinical data analysis. The framework...
In autonomous driving, recent research has increasingly focused on collaborative perception based on deep learning to overcome the limitations of in...
The Segment Anything Model (SAM), with its prompt-driven paradigm, exhibits strong generalization in generic segmentation tasks. However, applying S...
The purpose of anonymizing structured data is to protect the privacy of individuals in the data while retaining the statistical properties of the da...
At short distances between atoms, point charges are a poor approximation of the electrostatic interaction. Due to overlapping electron clouds, charges...
As modern computing advances, new interaction paradigms have emerged, particularly in Augmented Reality (AR), which overlays virtual interfaces onto...
Purpose To develop and evaluate a novel multitask deep learning framework for automated detection and localization of endoleaks at aortic digital subt...
The compounded effect of heavy rainfall and high tide backwater significantly exacerbate the load on urban drainage systems in coastal cities, leading...
Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with most patients eventually developing resistance to...
Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like tem...
PURPOSE: Current guidelines for thyroid radiation dose prescription lack uniformity and fail to consider the unique characteristics of individual pati...