BMC medical informatics and decision making
May 6, 2015
BACKGROUND: In this study we implemented and developed state-of-the-art machine learning (ML) and natural language processing (NLP) technologies and built a computerized algorithm for medication reconciliation. Our specific aims are: (1) to develop a...
Zhongguo fei ai za zhi = Chinese journal of lung cancer
Mar 20, 2025
BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surg...
Studies in health technology and informatics
Aug 22, 2024
This study introduces a novel approach for generating machine-generated instruction datasets for fine-tuning medical-specialized language models using MIMIC-IV discharge records. The study created a large-scale text dataset comprising instructions, c...
Studies in health technology and informatics
Jul 24, 2024
To construct a robot intelligent discharge follow-up platform and explore its application effects in clinical discharge follow-up scenarios Applying intelligent voice technology to build a robot intelligent discharge follow-up platform, replacing nur...
Natural language processing techniques are having an increasing impact on clinical care from patient, clinician, administrator, and research perspective. Among others are automated generation of clinical notes and discharge letters, medical term codi...
IMPORTANCE: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services.
The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare...
Studies in health technology and informatics
May 18, 2023
This paper aimed to detect the latent clusters of patients with opioid use disorder and to identify the risk factors affecting drug misuse using unsupervised machine learning. The cluster with the highest proportion of successful treatment outcomes w...