Studies in health technology and informatics
Jul 24, 2024
Our goal is to apply artificial intelligence (AI) and statistical analysis to understand the relationship between various factors and outcomes during pregnancy and labor and delivery, in order to personalize birth management and reduce complications ...
BACKGROUND: Recording and coding of ageing syndromes in hospital records is known to be suboptimal. Natural Language Processing algorithms may be useful to identify diagnoses in electronic healthcare records to improve the recording and coding of the...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Diabetic retinopathy (DR) is a serious complication of diabetes that can lead to vision impairment or even blindness if not detected and treated in the early stage. Recently, leveraging the electronic health records (EHR) data, machine learning-based...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic health records requires high throughput methods. Over the past 30 years, pr...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
During a patient's hospitalization, extensive information is documented in clinical notes. The efficient summarization of this information is vital for keeping healthcare professionals abreast of the patient's status. This paper proposes a methodolog...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Rising diabetes rates have led to increased healthcare costs and health complications. An estimated half of diabetes cases remain undiagnosed. Early and accurate diagnosis is crucial to mitigate disease progression and associated risks. This study ad...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich datasets for various disease analyses through advanced deep learning algorithms. However, the pervasive issue of missing values in EHRs significantly ham...
PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documenta...
PURPOSE: Patients with epithelial ovarian cancer (EOC) have an elevated risk for venous thromboembolism (VTE). To assess the risk of VTE, models were developed by statistical or machine learning algorithms. However, few models have accommodated deep ...
AIMS: To assess the predictive value of early-stage physiological time-series (PTS) data and non-interrogative electronic health record (EHR) signals, collected within 24 h of ICU admission, for traumatic brain injury (TBI) patient outcomes.
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