PURPOSE: The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool.
Studies in health technology and informatics
Jul 4, 2019
Clinical decision support systems are data analysis software that supports health professionals' decision - making the process to reach their ultimate outcome, taking into account patient information. However, the need for decision support systems ca...
PURPOSE: Cancer pathology findings are critical for many aspects of care but are often locked away as unstructured free text. Our objective was to develop a natural language processing (NLP) system to extract prostate pathology details from postopera...
Ultrasound (US) is a valuable imaging modality used to detect primary breast malignancy. However, radiologists have a limited ability to distinguish between benign and malignant lesions on US, leading to false-positive and false-negative results, whi...
PURPOSE: The Breast Imaging Reporting and Data System (BI-RADS) lexicon was developed to standardize mammographic reporting to assess cancer risk and facilitate the decision to biopsy. Because of substantial interobserver variability in the applicati...
Journal of the American Medical Informatics Association : JAMIA
May 1, 2019
OBJECTIVE: Decentralized privacy-preserving predictive modeling enables multiple institutions to learn a more generalizable model on healthcare or genomic data by sharing the partially trained models instead of patient-level data, while avoiding risk...
PURPOSE: Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model ...
The Journal of antimicrobial chemotherapy
Apr 1, 2019
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...
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