Latest AI and machine learning research in prescriptions for healthcare professionals.
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized medicine, pharmacogenomics, and AI-based strategies in optimizing patient outcomes with improved drug efficacy and reduced side effects. A comprehensive...
With an approximately 50% prevalence rate, medication nonadherence is a significant healthcare challenge that increases the risk of potentially avoidable adverse events and associated costs ranging from $949 to $44 190 per person annually. The ISPOR Medication Adherence and Persistence Special Interest Group conducted a systematic literature review (SLR) in 2023 to evaluate measures used in assess...
Visually impaired people face significant challenges when attempting to interact with and understand complex environments, and traditional assistive...
This study aims to guide language model selection by investigating: 1) the necessity of finetuning versus zero-shot usage, 2) the benefits of domain...
Conversational recommendation systems (CRSs) use multi-turn interaction to capture user preferences and provide personalized recommendations. A fund...
Diagnostic reasoning entails a physician's local (mental) model based on an assumed or known shared perspective (global model) to explain patient ob...
We introduce CO2, an efficient algorithm to produce convexly-weighted coresets with respect to generic smooth divergences. By employing a functional...
Working memory involves the temporary retention of information over short periods. It is a critical cognitive function that enables humans to perfor...
Drug-target interaction (DTI) prediction is a core task in drug development and precision medicine in the biomedical field. However, traditional mac...
Personalized food recommendation systems (Food-RecSys) critically underperform due to fragmented component understanding and the failure of conventi...
Robotic agents need to understand how to interact with objects in their environment, both autonomously and during human-robot interactions. Affordan...
Medication recommendation is crucial in healthcare, offering effective treatments based on patient's electronic health records (EHR). Previous studi...
To solve the safety problems caused by the restriction of interaction space and the singular configuration of rehabilitation robot in terminal tractio...
Task-Oriented Dialogue (TOD) systems are designed to fulfill user requests through natural language interactions, yet existing systems often produce...
Accurate 3D trajectory data is crucial for advancing autonomous driving. Yet, traditional datasets are usually captured by fixed sensors mounted on ...
Unresolved questions about how autonomous vehicles (AVs) should meet the informational needs of riders hinder real-world adoption. Complicating our ...
Large language models (LLMs) struggle with maintaining coherence in extended conversations spanning hundreds of turns, despite performing well withi...
Understanding bimanual hand interactions is essential for realistic 3D pose and shape reconstruction. However, existing methods struggle with occlus...
Non-adherence to medications is a critical concern since nearly half of patients with chronic illnesses do not follow their prescribed medication re...
Next-token prediction is the fundamental principle for training large language models (LLMs), and reinforcement learning (RL) further enhances their...