Latest AI and machine learning research in prescriptions for healthcare professionals.
Drug-side effect research is vital for understanding adverse reactions arising in complex multi-drug therapies. However, the scarcity of higher-order datasets that capture the combinatorial effects of multiple drugs severely limits progress in this field. Existing resources such as TWOSIDES primarily focus on pairwise interactions. To fill this critical gap, we introduce HODDI, the first Higher-...
Electronic Health Record (EHR) retrieval plays a pivotal role in various clinical tasks, but its development has been severely impeded by the lack of publicly available benchmarks. In this paper, we introduce a novel public EHR retrieval benchmark, CliniQ, to address this gap. We consider two retrieval settings: Single-Patient Retrieval and Multi-Patient Retrieval, reflecting various real-world ...
The increasing volume of drug combinations in modern therapeutic regimens needs reliable methods for predicting drug-drug interactions (DDIs). While...
Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual effects (VFX) serving as the powerhouse behind unforget...
White blood cells (WBC) are important parts of our immune system, and they protect our body against infections by eliminating viruses, bacteria, par...
Understanding the internal mechanisms of transformer-based language models remains challenging. Mechanistic interpretability based on circuit discov...
Medication adherence is critical for the recovery of adolescents and young adults (AYAs) who have undergone hematopoietic cell transplantation (HCT)...
The rapid evolution of large language models (LLMs) has transformed human-computer interaction (HCI), but the interaction with LLMs is currently mai...
Today's open vocabulary scene graph generation (OVSGG) extends traditional SGG by recognizing novel objects and relationships beyond predefined cate...
Map construction task plays a vital role in providing precise and comprehensive static environmental information essential for autonomous driving sy...
Objective: To evaluate the accuracy, computational cost and portability of a new Natural Language Processing (NLP) method for extracting medication ...
Autonomous personal mobility vehicle (APMV) is a new type of small smart vehicle designed for mixed-traffic environments, including interactions wit...
In response to the success of proprietary Large Language Models (LLMs) such as OpenAI's GPT-4, there is a growing interest in developing open, non-p...
Advanced persistent threats (APTs) are sophisticated cyber attacks that can remain undetected for extended periods, making their mitigation particul...
Detailed image captioning is essential for tasks like data generation and aiding visually impaired individuals. High-quality captions require a bala...
Guided diffusion-model generation is a promising direction for customizing the generation process of a pre-trained diffusion model to address specif...
The rise of single-cell sequencing technologies has revolutionized the exploration of drug resistance, revealing the crucial role of cellular hetero...
Natural Language Processing (NLP) has become a cornerstone in many critical sectors, including healthcare, finance, and customer relationship manage...
Large language models are increasingly customized through fine-tuning and other adaptations, creating challenges in enforcing licensing terms and ma...
Time constraints on doctor patient interaction and restricted access to specialists under the managed care system led to increasingly referring to c...