[HTML][HTML] A novel medical blockchain model for drug supply chain integrity management in a smart hospital
At present, in pharmacology one of the most serious problems is counterfeit drugs. The
Health Research Funding organization reported that in developing countries, nearly 10 …
Health Research Funding organization reported that in developing countries, nearly 10 …
[图书][B] Clinical text mining: Secondary use of electronic patient records
H Dalianis - 2018 - library.oapen.org
Hercules Dalianis Secondary Use of Electronic Patient Records Page 1 Hercules Dalianis
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …
Downstream task performance of BERT models pre-trained using automatically de-identified clinical data
Automatic de-identification is a cost-effective and straightforward way of removing large
amounts of personally identifiable information from large and sensitive corpora. However …
amounts of personally identifiable information from large and sensitive corpora. However …
[HTML][HTML] Recent advances in Swedish and Spanish medical entity recognition in clinical texts using deep neural approaches
R Weegar, A Pérez, A Casillas, M Oronoz - BMC medical informatics and …, 2019 - Springer
Background Text mining and natural language processing of clinical text, such as notes from
electronic health records, requires specific consideration of the specialized characteristics of …
electronic health records, requires specific consideration of the specialized characteristics of …
[HTML][HTML] Predicting sepsis onset using a machine learned causal probabilistic network algorithm based on electronic health records data
JK Valik, L Ward, H Tanushi, AF Johansson… - Scientific reports, 2023 - nature.com
Sepsis is a leading cause of mortality and early identification improves survival. With
increasing digitalization of health care data automated sepsis prediction models hold …
increasing digitalization of health care data automated sepsis prediction models hold …
[HTML][HTML] Using machine learning for predicting cervical cancer from Swedish electronic health records by mining hierarchical representations
R Weegar, K Sundström - PloS one, 2020 - journals.plos.org
Electronic health records (EHRs) contain rich documentation regarding disease symptoms
and progression, but EHR data is challenging to use for diagnosis prediction due to its high …
and progression, but EHR data is challenging to use for diagnosis prediction due to its high …
Multi-label diagnosis classification of Swedish discharge summaries–ICD-10 code assignment using KB-BERT
S Remmer, A Lamproudis… - Proceedings of the …, 2021 - aclanthology.org
Abstract The International Classification of Diseases (ICD) is a system for systematically
recording patients' diagnoses. Clinicians or professional coders assign ICD codes to …
recording patients' diagnoses. Clinicians or professional coders assign ICD codes to …
Validation of automated sepsis surveillance based on the Sepsis-3 clinical criteria against physician record review in a general hospital population: observational …
JK Valik, L Ward, H Tanushi, K Müllersdorf… - BMJ quality & …, 2020 - qualitysafety.bmj.com
Background Surveillance of sepsis incidence is important for directing resources and
evaluating quality-of-care interventions. The aim was to develop and validate a fully …
evaluating quality-of-care interventions. The aim was to develop and validate a fully …
[HTML][HTML] The economic burden of prostate cancer–a Swedish prevalence-based register study
S Hao, E Östensson, M Eklund, H Grönberg… - BMC health services …, 2020 - Springer
Background Incidence and prevalence of prostate cancer in Sweden have increased
markedly due to prostate-specific antigen (PSA) testing. Moreover, new diagnostic tests and …
markedly due to prostate-specific antigen (PSA) testing. Moreover, new diagnostic tests and …
[HTML][HTML] A classification framework for exploiting sparse multi-variate temporal features with application to adverse drug event detection in medical records
F Bagattini, I Karlsson, J Rebane… - BMC medical informatics …, 2019 - Springer
Abstract Background Adverse drug events (ADEs) as well as other preventable adverse
events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in …
events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in …