A Review of Biosensors and Artificial Intelligence in Healthcare and Their Clinical Significance
In the past decade, a substantial increase in medical data from various sources, including
wearable sensors, medical imaging, personal health records, and public health …
wearable sensors, medical imaging, personal health records, and public health …
A sco** review of using large language models (LLMs) to investigate electronic health records (EHRs)
Electronic Health Records (EHRs) play an important role in the healthcare system. However,
their complexity and vast volume pose significant challenges to data interpretation and …
their complexity and vast volume pose significant challenges to data interpretation and …
[HTML][HTML] Towards electronic health record-based medical knowledge graph construction, completion, and applications: A literature study
L Murali, G Gopakumar, DM Viswanathan… - Journal of biomedical …, 2023 - Elsevier
With the growth of data and intelligent technologies, the healthcare sector opened numerous
technology that enabled services for patients, clinicians, and researchers. One major hurdle …
technology that enabled services for patients, clinicians, and researchers. One major hurdle …
Artificial intelligence and biosensors in healthcare and its clinical relevance: A review
Data generated from sources such as wearable sensors, medical imaging, personal health
records, and public health organizations have resulted in a massive information increase in …
records, and public health organizations have resulted in a massive information increase in …
Big data and artificial intelligence in cancer research
The field of oncology has witnessed an extraordinary surge in the application of big data and
artificial intelligence (AI). AI development has made multiscale and multimodal data fusion …
artificial intelligence (AI). AI development has made multiscale and multimodal data fusion …
To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice
Objectives To develop recommendations regarding the use of weights to reduce selection
bias for commonly performed analyses using electronic health record (EHR)-linked biobank …
bias for commonly performed analyses using electronic health record (EHR)-linked biobank …
Arch: Large-scale knowledge graph via aggregated narrative codified health records analysis
Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as
both codified data and free-text narrative notes (NLP). The complexity of EHR presents …
both codified data and free-text narrative notes (NLP). The complexity of EHR presents …
Multisource representation learning for pediatric knowledge extraction from electronic health records
Abstract Electronic Health Record (EHR) systems are particularly valuable in pediatrics due
to high barriers in clinical studies, but pediatric EHR data often suffer from low content …
to high barriers in clinical studies, but pediatric EHR data often suffer from low content …
Strategies for secondary use of real-world clinical and administrative data for outcome ascertainment in pragmatic clinical trials
C Hau, PA Woods, AS Guski, SI Raju, L Zhu… - Journal of Biomedical …, 2024 - Elsevier
Background Pragmatic trials are gaining popularity as a cost-effective way to examine
treatment effectiveness and generate timely comparative evidence. Incorporating …
treatment effectiveness and generate timely comparative evidence. Incorporating …
[HTML][HTML] DOME: Directional medical embedding vectors from Electronic Health Records
Motivation: The increasing availability of Electronic Health Record (EHR) systems has
created enormous potential for translational research. Recent developments in …
created enormous potential for translational research. Recent developments in …