Latest AI and machine learning research in prescriptions for healthcare professionals.
Atherosclerosis (AS) causes thickening and hardening of the arterial wall due to accumulation of extracellular matrix, cholesterol, and cells. In this study, we used comprehensive bioinformatics tools and machine learning approaches to explore key genes and molecular network mechanisms underlying AS in multiple data sets. Next, we analyzed the correlation between AS and immune fine cell infiltrati...
PURPOSE: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more efficient NLP systems are needed to detect various symptoms and distinguish observed symptoms from negated symptoms and medication-related side effects. We evaluated the accuracy of NLP in (1) detecting 14 symptom groups (ie, pain, fatigue, swelling, d...
The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing eff...
Traditional Chinese medicine(TCM) placebos are simulated preparations for specific objects and the color simulation in the development of TCM placebos...
Blind individuals, who by necessity depend on screen readers to interact with computers, face considerable challenges in navigating the diverse and ...
While current personal smart devices excel in digital domains, they fall short in assisting users during human environment interaction. This paper p...
Integrating Generative AI (GenAI) into educational contexts presents a transformative potential for enhancing learning experiences. This paper intro...
Metabolic processes can transform a drug into metabolites with different properties that may affect its efficacy and safety. Therefore, investigation ...
Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and ...
In clinical treatment, identifying potential adverse reactions of drugs can help assist doctors in making medication decisions. In response to the p...
Discriminating between Parkinson's Disease (PD) and Progressive Supranuclear Palsy (PSP) is difficult due to overlapping symptoms, especially early ...
Combination therapy is a promising strategy for cancers, increasing therapeutic options and reducing drug resistance. Yet, systematic identification o...
Recent studies on learning-based sound source localization have mainly focused on the localization performance perspective. However, prior work and ...
The integration of Large Language Models (LLMs), especially ChatGPT, into education is poised to revolutionize students' learning experiences by int...
The extraction of biomedical data has significant academic and practical value in contemporary biomedical sciences. In recent years, drug reposition...
The convergence of the physical and digital realms has ushered in a new era of immersive experiences and seamless interactions. As the boundaries be...
Drug-target relationships may now be predicted computationally using bioinformatics data, which is a valuable tool for understanding pharmacological...
Significant interests have recently risen in leveraging sequence-based large language models (LLMs) for drug design. However, most current applicati...
Predicting signed interactions in biological networks is crucial for understanding drug mechanisms and facilitating drug repurposing. While deep gra...
A distinct feature of pancreatic ductal adenocarcinoma (PDAC) is a prominent tumor microenvironment (TME) with remarkable cellular and spatial heter...