This study trained long short-term memory (LSTM) recurrent neural networks (RNNs) incorporating an attention mechanism to predict daily sepsis, myocardial infarction (MI), and vancomycin antibiotic administration over two week patient ICU courses in ...
Artificial intelligence (AI)-based methods have emerged as powerful tools to transform medical care. Although machine learning classifiers (MLCs) have already demonstrated strong performance in image-based diagnoses, analysis of diverse and massive e...
The utility of a prediction model depends on its generalizability to patients drawn from different but related populations. We explored whether a semi-supervised learning model could improve the generalizability of colorectal cancer (CRC) risk predic...
As capabilities of predictive algorithms improve, machine learning will become an important element of physician practice and patient care. Implementation of artificial intelligence (AI) raises complex legal questions regarding health care profession...
This commentary responds to a hypothetical case involving an assistive artificial intelligence (AI) surgical device and focuses on potential harms emerging from interactions between humans and AI systems. Informed consent and responsibility-specifica...
Should an artificial intelligence (AI) program that appears to have a better success rate than human pathologists be used to replace or augment humans in detecting cancer cells? We argue that some concerns-the "black-box" problem (ie, the unknowabili...
PURPOSE: Segmentation of pulmonary nodules is critical for the analysis of nodules and lung cancer diagnosis. We present a novel framework of segmentation for various types of nodules using convolutional neural networks (CNNs).
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 29, 2019
This paper presents a fully developed computer aided diagnosis (CAD) system for early knee OsteoArthritis (OA) detection using knee X-ray imaging and machine learning algorithms. The X-ray images are first preprocessed in the Fourier domain using a c...
Due to recent advances in artificial intelligence, there is renewed interest in automating interpretation of imaging tests. Chest radiographs are particularly interesting due to many factors: relatively inexpensive equipment, importance to public hea...
BACKGROUND: Quantizing the Breast Imaging Reporting and Data System (BI-RADS) criteria into different categories with the single ultrasound modality has always been a challenge. To achieve this, we proposed a two-stage grading system to automatically...
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